Master of Science in Operational Research

Permanent URI for this collectionhttp://192.248.9.226/handle/123/68

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item: Thesis-Abstract
Modelling optimum water release for agricultural lands using goal programming approch
(2023) Rasangika, SAS; Samarathunga, DM; Edirisinghe, PM
The agricultural sector is one of the main sectors which benefits from several sources of water supply. This sector faces several challenges in securing water supply for its respective crops. Since the demand for water is increasing due to several factors, including population growth and an increased level of water dependent activities, and changes to crop selection influenced by various factors, including ever changing demand, the need for optimal use of water is identified as a priority for the rural agriculture sector in Sri Lanka. Past inflow data was used to obtain inflow values from the Udawalawa reservoir by using a forecasting model and the seasonal ARIMA model which was a statistical forecasting model used to forecast the inflow using RStudio software. In this respect water reservoir management is a crucial factor for allocating water for agricultural crops for study, a Goal programming model was formulated to determine the optimum water release for agricultural lands in Udawalawa region. Six main agricultural land divisions of the Udawalawa irrigation scheme were selected, and two of them received water from the right bank canal while the other four received water from the left bank canal of the Udawalawa reservoir. A Goal programming model with a 246 number of variables, 72 equality constraints, and 138 inequality constraints is solved using the MATLAB programming language and results show that water allocation from each reservoir can be used to fulfill the water demand throughout the year by using the water flow and allocation for each crop according to the priorities. In this case, it was assumed that 60% of the farming land used to cultivate paddy while the remaining 40% of the farming land used to cultivate other crops. These findings can be used by the stakeholders when making decisions on water allocation, not just based on the demand but also meeting a balance of crop selection. Key words: Water Release Optimization, Goal Programming, Forecasting
item: Thesis-Abstract
A Multi - product capacitated vehicle routing problem model with seasonality for the stationery industry
(2022) Liyanage RN; Gamage AIT
This dissertation presents an optimisation approach to deliver stationery commodities with highly seasonal demand. The problem is structured as a capacitated vehicle routing problem (CVRP) consisting of one distribution centre to numerous customer locations (one-to-many) with multi-products, where each customer requires various product mixes. A mixed-integer linear programming model was used to formulate the capacitated vehicle routing problem, and the Gurobi solver with customised heuristics algorithms was used to arrive at the solution. Intending to gain the advantage of separating the distributing points according to geographical areas, K means clustering was engaged. The solution generated through this model determined that annual distance has diversified by 44% between the peak and off-peak periods. The main findings show that the annual distance savings is around 28%, while the annual capacity saving is 22% when using the CVRP model compared to current practices. Further, it is determined that it is adequate to have 15 and 53 trips per week starting and ending at the distribution centre for off-season and season, respectively. Moreover, the route sequence of every vehicle was illustrated cluster-wise and season-wise separately. Two experiments were done, changing vehicle capacity and time horizon to have better outcomes, which will be additional guidance for the organisation. The dissertation offers a guide to improving the use of optimising techniques in the distribution network aiming at seasonal demand variations while providing a sound basis for future research directions.
item: Thesis-Abstract
Key factors influencing the optimum production by the glove knitting machine in a private company in Sri Lanka
(2021) Neroozan K; Edirisinghe PM
Knitting Machines of leading rubber manufacturing company was fully booked with glove knitting orders. So, the Excess capacities were outsourced within Sri Lanka or outside of Sri Lankan region. Since the company is Customer Centric Factory, the Profit margins came down due to the outsourcing the Capacity. So, the aim of this study was to analyse and determined key factors influencing the optimum machine production for specific products. Designed experiment was used to perform this analysis. Number of defectives used as the response variable. This will allow company to do the production in-house without outsourcing. This project contains study of four main factors and its effect on production and efficiency of the flat knitting machine based on minimal defect rate. The machine base, machine servicing activity, speed of the machine and the machine type plays an important role in knitting defects. The defect rates of knitted gloves were investigated using full factorial experimental design. The effect of machine base, machine servicing activity, machine speed and the machine type have been studied under four cases based on pareto principle. The four cases namely, Case I: 15G - Nylon, Case II: 13G - Thermostat, Case III: 13G – HPPE (High Performance Polyethylene), Case IV: 10G – HPPE. The results show that the machine base and the machine servicing have significant impact on the defects rate for all four cases, whereas, machine speed became significant for case II, III, and IV, as well as the machine type became significant impact for case IV based on linear terms. For 2-way interaction term, the machine base and the machine type have significant impact on the defects rate for case IV. The p-values of all four controlled parameters have been determined using ANOVA. The optimum parameters that correspond to the lower defects rate have also been evaluated.
item: Thesis-Full-text
Effect of agrochemical for paddy yield in Kalutara district: a regression approach
(2020) Perera BLN; Edirisinghe PM
Paddy is a major crop in Sri Lanka. Many farmers use Agro-Chemicals for their crops. Farmers believe that Agro-chemical increases the paddy yield. The objectives of the research were to: identify the effect of the fertilizer consumption to the paddy yield in Kalutara district; identify the effect of the pesticide usage to the paddy yield in Kalutara district, identify the relationship between paddy yield and fertilizer consumption, pesticide usage. Simple random sampling technique was used to select the sample of farmers. Regression analysis used as the analyzing technique for this specific study. The average fertilizer and pesticide usage around 622.5 kilograms per acre and 248.4-millilitres per acre respectively. The regression equation as follows: Log Paddy yield = 5.95 + 0.001458 Fertilizer consumption (KG per acre). The coefficient value for fertilizer consumption of the regression equation around 0.001458, With increment of one KG of fertilizer 0.001458 KG of paddy yield per acre can be expected to increase. According to the regression analysis fertilizer consumption positivity impact for the paddy yield while pesticide consumption negatively effects for the paddy yield. But to increase the paddy, yield the farmers use an acceptable level of fertilizer level and the pesticide level.
item: Thesis-Full-text
Analysis of the effect of broiler breeder's age on performance and behavior of chicken to forty - one days of rearing period
(2020) Karunarathne VLAD; Edirisighe P
The study was based on analysis of the effect of broiler breeder’s age on performance and behavior of chicken during the rearing period (41 days). Broiler chicks (1200 birds) from three different ages of broiler breeders (56 weeks, 72 weeks and 95 weeks (post molted breeder)) were studied for their body weight, feed conversion ratio (FCR), overall mortality rate and behavior for 41 days. The performance of the broiler was analyzed by considering the body weight, FCR and the overall mortality while eating, drinking, moving, laying were considered in behavior analysis. There were three experiment groups based on the age of broiler breeders and additional experiment group was made with mixed chicks from all the three breeders. Data were collected in weekly basis for the four experiment groups. Behavior of broilers was observed according to the scan sampling method at every five minutes interval. Data on body weight, FCR, mortality rate and behavior were analysed by using ANOVA. Mean values of body weight, FCR and behavior were separated by Tukey's Studentized Range (HSD) tests. Principal Component Analysis (PCA) was carried out in order to develop an overall behavior index by using sub behavior variables (eating, drinking, moving, laying, other behaviour). Results revealed that body weight of broilers was significantly different and the lowest body weight was found in the youngest breeder batch in the sixth week compared to the 72 weeks old breeder batch. The FCR was significantly different in the 4th week and the population mean FCR value of 56 weeks old breeder is greater than the 72 weeks old breeder. However, the overall mortality rate was not significantly different among all the breeder groups during the rearing period. The 72 weeks old broiler breeder group was identified as the best breeder group in terms of profit and the performance when the body weight values, FCR values, mortality rates and breeder maintenance cost are considered. According to the week wise analysis, the drinking behavior was significantly different among the breeder groups in the 6th week and the mean drinking amount of 95 weeks old breeder group was greater than the mixed aged breeder group. When the moving behavior is considered, it was significantly different among the breeder groups in the 6th week and the mean moving value of 72 and 56 weeks old breeders were greater than the mixed aged breeder group. Further, results revealed that the population overall behavior (overall behavior index value) was not significantly different during the rearing period and also there is no effect on performance of broilers by mixing of chicks from different age breeders. As a concussion, it was found in this study that the breeders’ age influences on the body weight, FCR, performance and some sub behavior parameters of broilers.
item: Thesis-Full-text
Impact of the job satisfaction on job performance of temporary academic staff :
(2020) Perera PGTN; Jayawardane T
Job satisfaction and job performance are the important phenomenon in human resource management in present world. The problem of this research is to find-out whether there is an impact on job satisfaction and dimension on job performance of the temporary employees working in the academic field of Sri Lanka. It will also investigate the relationship between the dimension of job performance and job satisfaction of the respondents as well as conduct a cross check of whether the former influences latter positive or negative in the long run. The research has been known for using a research framework with a pragmatic world view with survey strategy. This study has selected samples using stratified random sampling method and sample size has calculated using Taro Yamane method. 250 temporary academic staff members of the University of Kelaniya has been selected as the sample. This research is based on the analysis of primary data and data collected through structured questionnaire which was developed based on measurements to find results to the research problem by analyzing the previous researches. The data analysis process includes number of methods such as frequency, reliability, descriptive, regression and correlation. The sub component named learning environment highly contributed towards the job satisfaction while the evaluation system is the lowest contributing factor for the variable named job satisfaction. Communication between the university and employees is the most affected component on the job performance while the learning environment becomes the second important component. Need of the employees are the third important component and the emotional satisfaction about the job is the least important component while the evaluation system is not affected significantly. Research has found that there is high impact of job satisfaction on job performance of temporary academic staff.
item: Thesis-Full-text
Effect of socioeconomic and demographic factors on the household poverty in Sri Lanka: a logistic regression approach
(2020) Kalpage LU; Dissanayake R
poverty, it is needed to determine the basic needs of a household. This may be defined as narrowly as “those necessary for survival” or as broadly as “those reflecting the prevailing standard of living in the community”. Although Sri Lanka has downward trend in poverty, still considerable number of households are poor. Therefore, this study was trying to identify the determinants of the poverty of households in Sri Lanka. The major objective of this study is to identify the socioeconomic and demographic factors that mainly associated with household poverty in Sri Lanka. To accomplish the objective, Logistic Regression Model is used. Data gathered for the current study from Household Income and Expenditure survey (HIES) – 2016 conducted by the Department of Census and Statistics in Sri Lanka. According to the descriptive analysis of sample data of the HIES, 2.1% poor households are present. Out of these poor households, most of the poor households are in Batticaloa (10.5%). According to the results of Binary Logistic Regression Analysis, Residential Sector, Ethnicity of the household head, Education Level of the Household Head, Telephone facilities in the household area, Pipe borne line (main line) nearby household area, Any Household member engage to agricultural activity, Age of the Household Head and Household size are significantly effect on the probability of a poverty status of the household while gender of the household head, marital status of the household head, any of the household member receive income as an employee and household head suffer from chronic illness/disability are not statistically significant. The results of the study concluded that probability of being poor households increases with the living in rural area, uneducated household head, not having telephone facilities and pipe borne line in the living area, ethnicity of the household head is not Sinhala, no one of the household member is engaged to agricultural activity, larger household size and younger household heads. Also this study is recommended that the Sri Lankan government should pay more attention on the education of the people, utility facilities of the general public.
item: Thesis-Full-text
Developing a composite index to categorize manufacturing sector enterprises in Sri Lanka by using principal component analysis
(2020) Perera PPNAS; Dissanayake AR
The industry sector, manufacturing industries play a prominent role in accomplishing economic growth in countries all over the world. Presently, Sri Lanka does not have a commonly accepted standard to categorize manufacturing enterprises. Different organisations use different definitions and there is no consistency between them. The most common criterion is the number of persons employed in the company. Though this is simple, it disregards important characteristics such as annual turnover, assets, energy consumption, etc. Hence, an establishment with fewer employees and large turnover categorized into small scale establishment and the number of employees significantly large but turnover not sufficient to large scale categories also mark as a large scale enterprise. Therefore policy-making stage on small-medium enterprises (SME) very difficult to identify enterprises categories exactly. So, Identifying manufacturing sector enterprises on a generally accepted criterion is a long-felt necessity to the country. The main focus of this study is to develop a statistical method, to categorize manufacturing enterprises (5 or more persons engaged) in Sri Lanka. Developing a composite index and define the index boundaries to identify small, medium, and large manufacturing industries by considering the composite index mean value. One of the variable reduction methods called the principal component analysis (PCA) technique is used to define the index. Five reliable and significant variables were considered for the study. Data were collected from the Annual Survey of Industries 2017 (ASI) which is conducted by the Industries, Trade, Construction, and Services Division of the Department of Census and Statistics of Sri Lanka. 398 establishments out of the 1792 size sample were misclassified referred to two criteria (Turnover and Number of employees) as per the Ministry of Industry and Commerce (MOI) definition. Treating this misclassification is one of the main objectives of this study to come up with a solution.The analysis was addressed correctly to misclassified establishments in an accepted manner. Composite Index value less than or equal to zero (negative values) grouped as small scale and composite index value zero to 0.9983 categorized as meadium scale. Index values more than 0.9983 grouped as large scale establishments. Eventually, by introducing cut-off index value, a newly entered establishment could also be categorized. Further cut-off point can be re-valued by changing base year when an Economic Census being done. The introduction of a consistent methodology to categorize which led to granting aid for the right establishment and paying taxes from the right establishment, which is very important for the development of the country.
item: Thesis-Full-text
Factors affecting the severity of road accidents in Sri Lanka : a logistic regression approach
Seneviratna, NAMR; Cooray, TMJA
Road accidents have become a leading cause of death and injury as well as property damage worldwide. Ever increasing road accidents and traffic flow is a heavy burden to a developing country like Sri Lanka. In year 2016, 38915 accidents were reported where 7% of them are fatal contributing to 2824 deaths. Therefore, it is urgently needed to find solutions and reduce road accident deaths and injuries. The objective of this study is to identify the significant factors affecting for motorcycle and motor vehicle accidents in Sri Lanka. Secondary data used in this study between the period 2014 to 2016 were acquired from the police traffic headquarters, Colombo in Sri Lanka. A total number of 111457 road accidents where drivers at fault were included in the analysis. Among them 78531were motor vehicle accidents and 32926 were motor cycle accidents. Motorcycle accidents are analyzed separately due to high accident rate of motorcycles. Factors considered in the study were vehicle type, gender of driver, validity of license, accident cause, alcohol test, time of accident, weekday/weekend, road surface, weather condition, light condition, location and age of driver. Results revealed that male drivers (98%) have greater tendency to be involved in motorcycle and motor vehicle accidents rather than female drivers (2%). High number of motorcycle (75%) and motor vehicle (73%) accidents reported due to aggressive /negligent driving. Highest number of motor vehicle accidents (20.5%) reported by the drivers in between 29 - 34 years old. Highest number of motorcycle accidents (28.5%) reported by the drivers in between 19-24 years old. Majority of the accidents were occurred, while the vehicle was moving on a straight road. Among drivers and motorcyclists (7%) were found to have consumed alcohol. Most of motorcycle and motor vehicle accidents occurred in daytime under daylight on weekdays. Binary logistic regression is applied motorcycle and motor vehicles accidents separately to evaluate the odds of grievous accidents compared to non-grievous accidents. For motor vehicle accidents vehicle type, validity of license, time, location, alcohol test, accident cause, age of driver and gender have a significant effect on the severity of accidents. Bend or junction location, aggressive/negligent driving, drive by male drivers, drive at daytime, driving light vehicle and drivers who use alcohol below legal limit or no alcohol, have a high chance to be a grievous accident. Moreover, the older drivers have less accident risk. For motorcycle accidents, location type, time, age of driver, accident cause and gender have a significant effect on the severity of accidents. Among them, location type, accident cause and gender have an increasing effect on the probability of a grievous accident. Time and age of driver have a decreasing effect on the probability of a grievous accident. Straight road, aggressive/negligent driving, drive by male motorcyclists, daytime have a high chance to be a grievous accident. Moreover, the older motorcyclists have less accident risk. These findings can aid modifying regulations and laws and establishing preventive and protective approaches and strategies.
item: Thesis-Full-text
An Improved primal solution for the transportation problems in operational research
Linosh, NE; Daundasekera, WB; Cooray, TMJA
Organizations providing goods and services are mainly focusing on cost minimization within their organizations as it is a vital factor for their existence. In common, scheduling activities with less conflict within organizations is vital for their survival. In many organizations, transportation scheduling plays a major role in cost minimization. In particular, transporting goods from manufacturing plants to identified destinations with minimum transportation cost is knows as transportation scheduling or transportation problem. The objective of the transportation problem is to satisfy the destination requirements with minimum cost while satisfying the operating production capacity. Transportation problem is categorized as a Linear Programming problem. Generally, the Simplex method is the widely used method to solve Linear Programming problems. But, Simplex method is not the most efficient method to solve the transportation problem due to its special structure. Therefore, the most of the time effective and numerical efficient way to solve the transportation problem is Transportation Algorithm (TA) designed from the basic principles of Simplex method. The Transportation Algorithm consists of two major steps: obtaining the Initial Basic Feasible Solution (IBFS) and finding optimal solution using the IBFS. A better IBFS always reduces the number of iterations and computational time in finding the optimum solution. There are existing standard methods which are available to find the IBFS, but have failed to find an effective IBFS for the most of the transportation problems. To overcome this failure, in this research a modified heuristic approach is proposed to find a more promising IBFS. In the proposed method, the cumulative difference representation is used instead of cost matrix in order to make the assignments. This technique leads to assign most of the assignments at minimum cost. The cumulative difference representation represents the additional excess cumulative costs throughout the row and column for each possible cost of transportation. The IBFS found by the newly proposed method converges to the optimal solution faster than the standard methods considering the time consumed as well as less number of iterations to achieve it. The proposed method has proved to be in finding better IBFS for all the 70 transportation problems discussed in this study. The IBFS of 41 problems of selected 70 transportation problems them self are the optimal solutions. Further, for the rest of the 29 problems, the difference between IBFS and the optimal solution is only less than five percentage. Therefore, it can be concluded that the newly proposed method to find IBFS is robust in providing an improved primal solution compared to the existing standard methods.
item: Thesis-Full-text
Macroeconomic determinants of household expenditure in Sri Lanka : a multivariate co-integration approach
Wijesiri, MPMRB; Cooray, TMJA
The policymakers and economists in macroeconomics long have been given much attention on the factors determining the consumption expenditures because the level of consumption per person is often viewed as key measure of an economy’s productive success. This study is used to analyse the macroeconomic determinants of household consumption expenditure in Sri Lanka for the case of Sri Lanka in the post economic liberalization using multivariate co-integration approach. As macroeconomic variables gross domestic product, gross domestic savings, gross national income are used to this study. The sample period consists of annual data from 1978 to 2016. Vector error correction model and Johansen co-integration approach are used to identify long run relationships among gross domestic product, gross national income, gross domestic savings and household final consumption expenditure in Sri Lanka. The Johansen co-integration test proved that the natural log value of household final consumption expenditure is co-integrated with natural log values of gross domestic product, gross domestic savings and gross national income. Vector error correction model indicated that the existence of long run causality among natural log values of household final consumption expenditure, gross national income and gross domestic savings. Wald test is used to determine short run causalities among gross domestic product, gross national income, gross domestic savings and household final consumption expenditure in Sri Lanka. Wald test revealed that significant short run causalities with natural log values of household final consumption expenditure, gross domestic product, gross national income, and gross domestic savings.
item: Thesis-Full-text
Relations between macroeconomic variables and the stock market index : evidence from Sri Lanka
Aponsu, GMLM; Cooray, TMJA
This study examines whether the performance of Colombo Stock Exchange(CSE), as measured by the All Share Price Index (ASPI), is affected by a set of macroeconomic variables namely, Interest rate, Broad money supply, Index ofIndustrial Production and Inflation by using quarterly data obtained from Central Bank of Sri Lanka from 2004:QI to 20I6:Q3. The Vector. Autoregressive (VAR) framework was adopted by initially looking at the long run and short run relationship between stock market and the macroeconomic variables via the Johansen cointegration technique. To further explore the dynamic co-movement among the variables and the adjustment process towards the long run equilibrium, vector error-correction model (VECM) was used. Finally, Impulse Response Function (IRF) and Variance Decomposition (VDC) are employed in order to illustrate the importance of each macroeconomic variable to the stock market movement when a shock is imposed to the system. The analysis reveals that macroeconomic variables and the stock market index are co-integrated and, hence, a long-run equilibrium relationship exists between them. It is observed that the stock prices positively relate to the industrial production but negatively relate to inflation. The interest rate and money supply are found to be insignificant in determining stock prices in the long run. The results showed that both inflation and money supply significantly and inversely affect stock return in the short run. The results ofGranger causality test further indicate that there exists unidirectional causality from inflation to stock return. Furthermore, based on the results of impulse response function and variance decomposition analysis, it is confirmed that that stock market index has stronger dynamic relationship with industrial production index and inflation as compared to money supply and interest rate. Therefore Central Bank of Sri Lanka must undertake pragmatic policies aimed at controlling inflation within acceptable limits, since inflation is seen to inversely affect stock return.
item: Thesis-Full-text
Time series forecasting of post-war tourism prospects for Sri Lanka
Gnanapragasam, SR; Cooray, TMJA
Tourism plays a big role in the development of a country in terms of economics as it is one of the biggest and fastest-growing economic sectors in the world. It accounts for a large part of Gross Domestic Product of any country through Foreign Exchange. This study focused on international tourist arrivals to Sri Lanka. In the past, nearly three decades, Sri Lanka had to face conflict within the country. Tourists had less interest of visiting Sri Lanka, mainly due to the uncertainty of security. Nevertheless, the internal conflict is over and tourist arrivals have dramatically increased over last six years. The aim of this study is to investigate the impact of internal conflict in Sri Lanka for tourist arrivals by splitting the entire time frame by before and after the conflict as two windows. Further this study discusses the factors which are influenced by tourism in Sri Lanka. The data for the study is extracted from the annual reports of the Sri Lanka Tourism Development Authority. Time series models are developed in two separate time windows by using the methods: HoltWinters’ Exponential Smoothing, Seasonal Autoregressive Integrated Moving Average (ARIMA) modeling, State Space modeling and Dynamic Transfer Function modeling. All necessary tests are carried out for model development, diagnostic checking and forecast. In the empirical study, behavior of arrivals with its trend and seasonal patterns are analyzed, best models are developed based on the accuracy of fitted models in terms of Mean Absolute Percentage Error (MAPE) values and the impact ofthe factors influenced by tourism are deeply discussed. MAPE values for the recommended models for after the conflict arc less than 7%. In both windows, Seasonal ARIMA method performs the best. Moreover it is estimated by ex-post forecast that, 2.085 million international tourist arrivals can be expected in the year 2016.
item: Thesis-Abstract
An Improved approach to line balancing for garment manufacturing
Wickramasekara, AN
Most of the time, production managers in the garment industry are unable to complete the orders at the scheduled time. One ofthe reasons is the unavailability of a Line Balancing procedure that could encompass the stochastic nature of the garment manufacturing process, which is manifested through the likes of variability of operating times, machine breakdowns, reworking and breaks of operators The objective of this research is to introduce a new line balancing procedure through giving due consideration to the above mentioned stochastic nature of the process. Having selected a sewing line which consists of experience operators in a garment factory, the process times of operations, time spent for selected non value added activities were recorded. After that, probability distributions were fitted for each operation. In addition to processing times, hypothetical probability distributions were assumed with regard to breaks of operators. Next, an initial algorithm was developed. Afterwards, the work of each operator was modelled in Arena in order to test the algorithm. Then, the initial algorithm was developed by adding different activities in order to make all decisions with regard to work allocation so that the expected line target is achieved with minimum number of operators. The first step ofthe algorithm is collecting necessary information (order size, available time for the production, cycle times of operations, and types of failures of resources). Second step is estimating Standard Probability Distributions with regard to operations, failures of resources and determining the required production rate. Third step is developing the precedence diagram for the manufacturing process. Next step is simulating the work of workstations after assigning one operator and one feasible operation to them. Afterwards, the number of operators and number of operations required for workstation is finalized based on the analysis ofsimulated daily production quantity. In order to use this algorithm in the real world, a data base should be maintained to record cycle times, types of failures of resources, up times and down times with a view to estimate probability distributions. Moreover, this algorithm assumes every operator is multi skill and performs consistently.
item: Thesis-Abstract
Evaluation of optimum time for planning, scheduling and resource allocations of new ship construction project at colombo dock yard
Bandara, BMCSH; Cooray, TMJA
GOOD PLAN OF THE JOB IS HALF THE JOB. As of this statemenl the present scenario of working scheduling and project tracking is augmented with large projects such as new ship building projects. Building a new vessel can be considered as a high-tech job which is actually a project with a deadline and a dedicated team. Project manager is the leading person and the holder ofthe main responsibility to deliver the project under the stipulated time and budget with the required quality. Project manager equipped with the authority to acquire any resource to complete the project by coordinating with the other departments and acts as the operational in charge of every engineer under the other departments in a matrix organizational structure. 'Phis is aimed to evaluate optimum time for planning, scheduling and resource allocation for future new ships construction projects at Colombo Dock Yard (CDL). All the previous data have taken by consecutive past three sister vessels for calculations and Critical Path Method (CPM) and Program Evaluation and Review Technique (PERT) used to find critical path and critical activities. More information about which activities are “critical”, meaning that they have to be done on time or else the whole project will lake longer. This report indicated that what those are. Also this report illustrated that the way to schedule human resource without disturbing that critical activities and smoothen the resources accordingly. In addition, though the collection of information the study can emphasize the idea about the CPM and PERT applied in the shipping industry. The shipbuilding project planner should consider the uncertainty during scheduling and the above results have implications for manager’s decision makings.
item: Thesis-Abstract
Identification of district level prosperity indicators of Sri Lanka
Rajamohan, KR; Peiris, TSG
There are several indicators to measure the economic development of a nation such as Gross Domestic product (GDP), Human Development Index (HDI) and Human Poverty Index (HPI) etc. In 2008 the Central Bank of Sri Lanka introduced an index to measure the provincial prosperity of Sri Lanka. The suitability ofthis indicator in measuring the provincial development is questioned by many critiques, due to various drawbacks. Further, this index cannot be used for district levels This study aims to suggest the Human Development Index (HDI) and Human Poverty Index (HPI) for the districts of Sri Lanka using the national level data and further this study aims to identify the weaknesses of the present Sri Lanka’s prosperity index (SLPI) and formulate a new refined prosperity index for districts in Sri Lanka. The HDI and HPI are estimated using the methodology proposed by the Human Development Report ofthe UNDP and the districts were ranked according to the estimated HDI and HPI values. The suitability of these indicators is verified by the variation of HDI and HPI between the districts in specific time periods. The new refined prosperity index was formulated by correcting the conceptual weaknesses in SLPI. New variables were included in the new refined index. These variables were statistically analyzed using principal component analysis and factor analysis. The research findings reveal that the HDI has several weaknesses in measuring the regional development. The weaknesses are the inappropriate estimation methodology ofHDI and the slowly changing nature of the variables included in the HDI. Another weakness is the low weight given to the GDP index of the HDI, which covers more aspects of development. The HPI shows significant variations throughout the time periods as well as between districts. This is due to the appropriate estimation methodology ofHPI and the suitability ofvariables included in the HPI to capture the multi-dimensional perspective of the poverty. Therefore, instead of HDI, the HPI could be used as an indicator ofregional poverty levels. The new refined index is a conceptually stronger index than the SLPI as it covers all aspects of prosperity and provides the sector performance of different districts.
item: Thesis-Full-text
Analysis of the relationship between exchange rate, inflation rate and gold price of Sri Lanka:
Karunawardana, KMEM; Cooray, TMJA
Recent records show that the price of gold has been rising at a higher rate than in the past. This has been shown to be true for Sri Lankan gold prices as well. In this study an attempt has been made to develop a forecasting model for gold price and to examine the relationship between selected factors, that is the inflation rate, exchange rate and gold price. The data was mined from the World Gold Council and the Central Bank of Sri Lanka. The sample data of gold price were gathered from 2007 January to 2016 March in the currency of US dollars per troy ounce. It was converted into Sri Lankan rupees per 22 carat. Data until December 2015 were used to build the ARIMA model and the VEC model remainder was used to forecast the gold price and to check the accuracy of the model. Box-Jenkins, Auto Regressive Integrated Moving Average methodology (ARIMA) has been used to developed the model 𝐷[𝐿𝑛[𝐺𝑂𝐿𝐷 𝑃𝑅𝐼𝐶𝐸]]; with terms AR (3) and MA(3) and to forecast the future gold price. The MAPE value of fitted data in the appropriate model is 9.4%. To identify the relationship with gold price, inflation rate and exchange rate, quarter value data of all three factors were used. Two models were developed by based on the minimum AIC and the minimum SIC values. Firstly, the stationarity of the data is checked through the Augmented Dickey Fuller test and then the Johansen co-integration test and the Vector error correction model (VECM) are employed for analysis. The results of the Johansen co-integration test revealed that exchange and inflation rates are co-integrated with the gold price that led to run VECM. The VEC model developed for minimum AIC value provides evidence for the existence of long run and short run relationships between the gold prices, the exchange rate and the inflation rate and the model developed for minimum SIC value as well. The model developed based on minimum SIC value is rejected since the existence of serial correlation. The speed of adjustment to equilibrium is 12.1%, the model explains the gold price of the current quarter as 69.3% of the gold price of the previous quarter, and the exchange and inflation rates in the VEC model developed based on minimum AIC value. The MAPE value of fitted data from appropriate VEC model is 6.36%. When forecasting time period is increasing the percentage error in ARIMA model is higher than the percentage error increasing in appropriate VEC model. According to the mean absolute percentage error as forecasting accuracy measure the study concluded that the VEC model is more appropriate fitted model to forecast the gold price in Sri Lanka than the fitted ARIMA model.
item: Thesis-Abstract
Preventive maintenance model for automated filling machine
Wijesekera, AK; Cooray, TMJA
Maintenance, repair, and operations are very crucial factors for both manufacturing and service industries. Methodologies like Preventive Maintenance (PM), Planned Maintenance, and Predictive Maintenance deal well with the issues ofmaintenance all over the world. Preventive maintenance is a schedule of planned maintenance actions aimed at the prevention of breakdown and failures. The principle of PM is identified as “prevention is better than cure”. Sri Lankan industries too have identified the importance of preventive maintenance. This research is carried out to develop a preventive maintenance model for an automated filling machine for a well-known yoghurt manufacturing company in Sri Lanka. Trouble choosing areas were production output delays due to machine breakdowns and due to other various reasons such as poor maintenance planning and inefficiency in money spending on maintenance activities etc. This report evaluates the maintenance policy that has been applied in the company. Theory of Weibull and Dodson’s tabular solution were used to build a preventive maintenance models and to find optimum time between PM actions for critical components. New PM schedule was implemented after determine the optimum time for PM actions. The importance of a maintenance policy for a company and the benefits of keeping past maintenance records are highlighted in this report. Further new method of implementing PM model and PM schedule was also introduced. Moreover, these models will be beneficial to all other departments of a company other than maintenance department. Maintenance, repair, and operations are very crucial factors for both manufacturing and service industries. Methodologies like Preventive Maintenance (PM), Planned Maintenance, and Predictive Maintenance deal well with the issues ofmaintenance all over the world. Preventive maintenance is a schedule of planned maintenance actions aimed at the prevention of breakdown and failures. The principle of PM is identified as “prevention is better than cure”. Sri Lankan industries too have identified the importance of preventive maintenance. This research is carried out to develop a preventive maintenance model for an automated filling machine for a well-known yoghurt manufacturing company in Sri Lanka. Trouble choosing areas were production output delays due to machine breakdowns and due to other various reasons such as poor maintenance planning and inefficiency in money spending on maintenance activities etc. This report evaluates the maintenance policy that has been applied in the company. Theory of Weibull and Dodson’s tabular solution were used to build a preventive maintenance models and to find optimum time between PM actions for critical components. New PM schedule was implemented after determine the optimum time for PM actions. The importance of a maintenance policy for a company and the benefits of keeping past maintenance records are highlighted in this report. Further new method of implementing PM model and PM schedule was also introduced. Moreover, these models will be beneficial to all other departments of a company other than maintenance department.
item: Thesis-Abstract
Development of an algorithm for optimum allocation of multiple teams to borehole drilling sites
Dilanthi, UN; Dissanayake, DMDOK
Borehole drilling is one of the geotechnical investigations for foundation designing process of the construction industry. The growth ofthe construction industry requires an effective utilization of borehole drilling teams for the borehole drilling sites. It is similar to sending multiple travelling salesmen for multiple locations under the minimum over all travelling distance. In the borehole drilling, there are mainly two types of borehole drilling teams: wash boring teams and wash boring/ core drilling teams. And there are different accessible time periods for the sites. The service time of the locations are different and it can be predefined from the nature (number of holes, ground conditions, drilling length... etc.) of the drilling site job. It is expected that the difference ofthe total work duration among teams should be in an accepted level of difference. The research outcome was an algorithm to provide a heuristic solution, answering which team does which job and when it is. Initially, filtering the job list was done, to group similar type ofjobs together and, then groups the jobs, which require completion before the shutdown of the drilling teams. Clustering the two dimensional drilling sites to given number of teams were done to separate the jobs among the drilling teams. The outcome drilling site clusters total service time duration differences were minimized to a given accepted difference level by iteratively shifting jobs from the cluster, which has maximum total service time duration. This balancing was done with the minimum effect to the mean distance to the cluster centroids and avoiding oscillating between intermediate solutions ofthe iterations. The drilling site locations distance matrices were modified by adding the ‘office location’ and replacing ‘big M’ values for main diagonal distances of each outcome cluster and, sent through the Hungarian method, which is used for solving assignment problem in operational research. The outcome of the Hungarian method is the shortest path or set of sub routes. One of the distances of a respective two locations containing sub routes was replaced with ‘big M’ and rerunning through the Hungarian method was done. The graphical representations of given sub routes were taken as a guide for designing of the shortest path of each clustered drilling sites. When the number of drilling sites in a cluster is higher than ten, the given approach will become tedious, but in the geotechnical investigations industry it is not ranging higher than ten. The above mentioned algorithm of allocation of drilling teams to multiple drilling sites, were shown better optimization over the traditional practice of ‘instant team allocation for nearest location’.
item: Thesis-Abstract
Identifying the factors for customer dissatisfaction through customer complaints
Manjula, JLP; Peiris, TSG
Banks in Sri Lanka play a key role in the economy by serving a vast array of needs of customers such as holding deposits, handling withdrawals, making loans and more. It is evident that banks are under intense pressure to remain profitable in today's volatile economic climate. The complexity of the banking business is driven with the introduction of new products/services and processes which are facilitated through ongoing technological advancements. The expectations of customers also shift to a higher platform and the comparisons are made with the experiences gained while dealing with competitors. Thus the challenges in retaining customer base are paramount to every bank since the business environment is more dynamic and competitive as the customers are the major stakeholders of the banking system. Therefore the customer service is one ofthe key factors in the banking industry. This study was done to identify the factors for customer dissatisfaction through customer complaints of a leading licensed specialized bank in Sri Lanka using customer complaint data ofthe bank’s call centre. In order to identify common factors, data were analysed using Factor Analysis (FA) and the factors were rotated using three different orthogonal rotations. The analysis found two-factor model is the most suitable model to explain the variability ofselected six variables from the database of customer complaints. The adequacy for FA was tested using KMO statistic (KMO= 0.777) and the Bartlett’s Test of Sphericity (p = 0.000). The communalities of each variables were closed to one. The results were invariant irrespective ofrotation method. The identified two factors can be named as ‘Reliable Response’ and ‘Knowledgeable Attention’. The Reliable Response (first factor) is a combination of variables namely ‘Errors in Transactions’, ‘Delays in Operations’, ‘Less Helpful’ and ‘Less Trusting’. The Knowledgeable Attention (second factor) is a combination of variables namely ‘Less Personnel Attention’ and ‘Poor Product Knowledge’. The rank correlations between the total number of complaints and ‘Reliable Responding’, the total number of complaints and ‘Knowledgeable Attention’ are not very strong (r^ 1.0), even though they are significant .It implies that identified two factors separately are more informative and meaningful than considering total number of complaints. Banks in Sri Lanka play a key role in the economy by serving a vast array of needs of customers such as holding deposits, handling withdrawals, making loans and more. It is evident that banks are under intense pressure to remain profitable in today's volatile economic climate. The complexity of the banking business is driven with the introduction of new products/services and processes which are facilitated through ongoing technological advancements. The expectations of customers also shift to a higher platform and the comparisons are made with the experiences gained while dealing with competitors. Thus the challenges in retaining customer base are paramount to every bank since the business environment is more dynamic and competitive as the customers are the major stakeholders of the banking system. Therefore the customer service is one ofthe key factors in the banking industry. This study was done to identify the factors for customer dissatisfaction through customer complaints of a leading licensed specialized bank in Sri Lanka using customer complaint data ofthe bank’s call centre. In order to identify common factors, data were analysed using Factor Analysis (FA) and the factors were rotated using three different orthogonal rotations. The analysis found two-factor model is the most suitable model to explain the variability ofselected six variables from the database of customer complaints. The adequacy for FA was tested using KMO statistic (KMO= 0.777) and the Bartlett’s Test of Sphericity (p = 0.000). The communalities of each variables were closed to one. The results were invariant irrespective ofrotation method. The identified two factors can be named as ‘Reliable Response’ and ‘Knowledgeable Attention’. The Reliable Response (first factor) is a combination of variables namely ‘Errors in Transactions’, ‘Delays in Operations’, ‘Less Helpful’ and ‘Less Trusting’. The Knowledgeable Attention (second factor) is a combination of variables namely ‘Less Personnel Attention’ and ‘Poor Product Knowledge’. The rank correlations between the total number of complaints and ‘Reliable Responding’, the total number of complaints and ‘Knowledgeable Attention’ are not very strong (r^ 1.0), even though they are significant .It implies that identified two factors separately are more informative and meaningful than considering total number of complaints.