Browsing by Author "Perera, HN"

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Assessing the impact of lean and agile supply chain strategies on effective covid-19-mass vaccinations
(Sri Lanka Society of Transport and Logistics, 2022-08) Gomes, K; Perera, HN; Perera, N; Thibbotuwawa, A
A properly designed vaccine supply chain that uses suitable supply chain strategies can facilitate an effective mass vaccination that minimises COVID-19 infections and deaths. This study assesses the impact of two supply chain strategies which are Lean supply chain strategy and Agile supply chain strategy on effective mass vaccination using a two-stage approach. In the initial stage, we developed an optimal vaccine distribution network under both Lean and Agile supply chain strategies separately, for a selected scenario in Colombo, Sri Lanka. In the second stage, we have developed a Susceptible-Exposed-Infected-Recovered (SEIR) model for COVID-19 which reflects the impact on infections and deaths when using the two different supply chain strategies. Results of this study reflect that a higher percentage of lead time saving can be achieved when using the Agile supply chain strategy. Moreover, when using Agile strategy, a considerable reduction of infections and deaths can be expected for the considered scenario despite a cost accumulation of approximately 32%.
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Challenging factors to adopt circular economy in sustainable food supply chain
(IEEE, 2022-07) Pannila, N; Jayalath, MM; Thibbotuwawa, A; Perera, HN; Rathnayake, M; Adhikariwatte, V; Hemachandra, K
Even though circular economy has captured global attention recently with its sustainable implications, the adoption takes a much slower approach, particularly in the food supply chain. This study attempts to identify challenging factors that hinder the adoption of circular economy in the food supply chain. A total of 17 challenging factors are identified via a systematic literature review. The challenging factors were grouped into 6 categories: economic, social, institutional, technological and informational, supply chain, and organizational. Literature frequency analysis method combined with an article-level research citation metric of field-weighted citation impact was employed to prioritize the challenging factors based on the literature importance. Thus, the findings reveal that cost efficiency considerations, less enforcement of legislation and regulations, and no long-term shared vision among stakeholders are the three most critical challenging factors to adopt circular economy in the food supply chain. The findings will help managers, decision-makers, practitioners, and governments to formulate policies and strategies to implement circular practices in the food supply chain effectively.
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Comparing different metaheuristic methods in solving a real-world application of vehicle routing problem
(Sri Lanka Society of Transport and Logistics, 2022-08) Fernando, WM; Thibbotuwawa, A; Perera, HN
This research applied an extension of the Vehicle Routing Problem (VRP) to optimize the distribution processes of a supermarket chain. This model is a combination of CVRP (Capacitated VRP), MDVRP (Multi-depot VRP), and HFVRP (Heterogenous fleet VRP). The applied model aims to minimize the distribution cost of the selected supermarket chain. All the constraints of the VRP model were defined based on the operational practices of the application. The research aimed to compare the performances of three metaheuristic methods, Simulated Annealing (SA), Tabu Search (TS), and Guided Local Search (GLS) in optimizing the real-world application. Results highlighted that GLS outperformed in terms of the quality of the solutions and the computation time in optimizing the selected distribution network. This research is significant because it tests both the VRP model and the three metaheuristic methods using a real-world industry application.
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E-procurement awareness and adoption: a Sri Lankan perspective
(Sri Lanka Society for Transport and Logistics, 2016-06) Rajasooriyar, C; Perera, HN; Gunaruwan, TL
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Factors influencing the implementation of green supply chain management practices in a supermarket: a Sri Lankan case
(Sri Lanka Society of Transport and Logistics, 2021-10) Sugathadasa, PTRS; Hewage, HC; Perera, HN; Dharmarathna, D; Gunaruwan, TL
Green Supply Chain Management has emerged as one of the key industry trends in the supermarket sector. Adoption of Green Supply Chain Management in supermarkets is a challenging process that should be implemented along with many stakeholders such as manufacturers, suppliers, and customers. This study analyses the key influential factors for the implementation of Green Supply Chain Management practices in supermarkets. This study was carried out focusing on a leading supermarket chain in Sri Lanka. First, an extensive review of literature, and unstructured interviews with industry personnel were conducted to identify the key influential factors. Then, a questionnaire was distributed among the industry practitioners to rank the identified factors based on a Likert scale. Finally, this study shows seven key factors to consider when implementing Green Supply Chain practices in supermarkets.
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Fertilizer policy intervention and agriculture supply chain sustainability: an investigation of impacts of the chemical fertilizer ban on farmers in sri lanka
(Sri Lanka Society of Transport and Logistics, 2023-08-26) Perinparajah, V; Jayalath, MM; Perera, HN; Gunaruwan, TL
There has been an immediate change in fertilizer policy in 2021 in Sri Lanka. Sri Lankan government has limited and banned the import of fertilizers and agrochemicals with the objective of making its agriculture 100% organic. Sri Lanka’s leading agricultural economists and experts have indicated that this fertilizer policy reform will lead to a dramatic drop in agriculture production and has adverse impacts on farm incomes and farming families. This research aims to investigate it through a longitudinal analysis of the data to verify whether the fertilizer policy reforms have a negative impact on agricultural productivity and more importantly on the welfare of farmers. The empirical data has been collected from farmers by interviewing them face to face. Results shows that this fertilizer policy change leads to major yield losses and farmers’ livelihoods have been highly affected. This study could serve as a starting point for future studies that revolve around upcoming fertilizer policy reforms.
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Fuel stacking and stove choice decisions: a discrete choice model of Sri Lankan household preferences for clean cooking solution
(IEEE, 2022-07) Dissanayake, BI; Perera, HN; De Silva, MM; Rathnayake, M; Adhikariwatte, V; Hemachandra, K
Transition from non-clean cooking fuels to clean cooking fuels is a sustainable development requirement which needs to be addressed at a household level. Household decisions play a crucial role in terms of cooking transition and preference towards product specific factors. Developing countries need to address this problem immediately as it faces socioeconomic challenges which are complex. The presence of improved consumer products according to consumer’s preference for cooking fuels in these regions acts as a major motivator for cookstove adoption. Hence, understanding household preference for clean cooking solutions is useful for policy makers and organisations involved with the cooking fuel supply chain and product development. In order to better understand household decision-making in Sri Lanka, a stated preference survey and discrete choice model were constructed. With the exception of price and usage cost factors for the dirty stacking households, the study indicated that the product-specific factors explored have a significant impact on stove and fuel choices. Instead, energy switching, in which LPG and electricity supplement and increase a household's energy portfolio, is more likely.
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The impact of renewable energy forecast errors on imbalance volumes and electricity spot prices
(Elsevier, 2019) Goodarzi, S; Perera, HN; Bunn, D
This paper contributes to the general consideration of whether a policy of incentivising system operators to improve the quality and market availability of forecasts for renewable energy outputs would be beneficial. Using data from the German electricity market, we investigate the effect of wind and solar energy forecasts errors on imbalance volumes and subsequent spot electricity prices. We use ordinary least squares regression, quantile regression and autoregressive moving averages to identify these relationships using variables that have a quarter-hourly data granularity. The results show that higher wind and solar forecast errors increase the absolute values of imbalance volumes and that these can pass through into higher spot prices. We find that wind forecast errors in Germany impact spot prices more than solar forecasting errors. Policy incentives to improve the accuracy and availability of renewable energy forecasts by the system operators should therefore be encouraged.
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Impacts of the first COVID-19 lockdown on mobility and consumption of households in Sri Lanka : results of a survey
(2021) De Silva, MM; Perera, HN; Kumarage, AS
Sri Lanka was introduced to an unnamed virus on 27th January 2020 when a Chinese tourist was diagnosed with it [1]. Within 8 weeks, the virus named COVID-19 had begun infecting the local population, and the government was taking measures to prevent its spread in Sri Lanka.
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Inventory allocation behavior of the distributor during demand shocks and supplier disruptions
(Sri Lanka Society of Transport and Logistics, 2023-08-26) Kosgoda, D; Perera, HN; Aloysius, J; Gunaruwan, TL
Inventory allocation is one of the main operations in any supply chain. Most of the time inventory allocation for the retailer is done by the manager of the distribution center. Literature reports three allocation mechanisms namely; proportional, linear, and uniform which can be used by the distributor when allocating inventory to their retailers. However, the distributor struggles to identify the best allocation mechanism when there is a mismatch between available supply and demand. We investigate the inventory allocation behavior of the distributor under three different scenarios; (i). when there are positive demand shocks, (ii) when there are supply disruptions, and (iii) when there are both scenarios. We used a computerized laboratory experiment to study the allocation behavior. We employed undergraduate students as participants in our laboratory experiment. The participants in all treatments were assumed as distributors and they were asked to allocate the inventory using any inventory allocation mechanism out of the three mechanisms. ANOVA techniques were used to analyze our data. Our results suggest, the proportional allocation mechanism as the best allocation mechanism when there are demand spikes. A liner allocation mechanism is ideal to use when there are supply disruptions. Further, when there are both demand spikes and supply disruptions, we recommend using the liner allocation mechanism.
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Inventory decisions under stochastic demand scenario with high inflation rate-ml approach
(Sri Lanka Society of Transport and Logistics, 2023-08-26) Siriwardena, V; Kosgoda, D; Perera, HN; Gunaruwan, TL
Hyperinflation is a situation where prices increase at an average monthly rate of 50% or more, leading to a rapid loss of the currency’s value and causing severe economic problems. Inventory decisions under hyperinflation are crucial due to the high level of uncertainty and the rapid increase in prices can lead to significant losses if inventory is not properly managed. We examine the effects of hyperinflation on inventories of Biscuits and develop an ML model to forecast optimal order quantities of Biscuit products, with the intention of lowering inventory holding costs and inventory deterioration. Data from a retail company in Sri Lanka during the hyperinflation period of 2022 have been used to develop the ML model to predict customer demand. Six ML techniques were utilized to achieve the research objectives. Root Mean Squared Error (RMSE) and R-squared metrics are employed to choose the best model. We find that Random Forest is the most appropriate ML model to forecast optimal order quantities during a hyperinflation situation. The outcomes of our study will aid professionals working in the Biscuit industry to effectively handle inventory management during periods of hyperinflation. Our ML model can serve as a fundamental tool for predicting inventory levels during hyperinflation, which can be used as a starting point for further analysis.
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Longitudinal analysis of supply chain transformation project management : case based learnings from the Sri Lankan manufacturing sector
(2017) Perera, HN; Sudusinghe, JI
This empirical study investigates three supply chain transformation projects in Sri Lanka. Building on two previous studies, this study attempts to discern the imperatives and essentials of a successful supply chain transformation project. In essence, this study retrospectively scrutinizes the outcomes of supply chain transformation projects commenced a minimum of 5 years earlier. By juxtaposing the outcomes with longitudinal data from of the said projects, the authors draw unique insights on the dynamics of managing a supply chain transformation project. Additionally, this study outlines critical factors that need to be taken into consideration when implementing supply chain transformation projects. Furthermore, this study improves and outlines the supply chain project management process outlined in previous studies [1]. In sum, this study connects the two growing fields of Supply Chain Management and Project Management in order to posit the importance of expanding the understanding of supply chain project management.
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Managing supply chain transformation projects in the manufacturing sector: case-based learning from Sri Lanka
(Sri Lanka Society for Transport and Logistics, 2016-06) Perera, HN; Thibbotuwawa, AIG; Rajasooriyar, C; Sugathadasa, PTRS; Gunaruwan, TL
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Maritime logistics research in South Asia: a systematic review
(Sri Lanka Society of Transport and Logistics, 2021-10) Weerasinghe, BA; Perera, HN; Gunaruwan, TL
Systematic reviews are trending because they inform future studies by providing a snapshot of the existent research within the relevant field. We found a dearth of systematic reviews and bibliometric analysis in maritime logistics. This study discusses the contributions of authors based in South Asia to research in maritime logistics. Moreover, maritime logistics research in this geographic region needs to be examined in the context of South Asia’s emergence as a geopolitical and maritime hub. This review reveals that an overwhelming majority of research on maritime logistics in South Asia originates from India. This review identifies five research clusters on examining networks between authors and countries. These were derived based on author keywords found in the pool of research using systematically derived through Scopus. We find that, among the South Asian research on maritime logistics, research focusing on the Indo-Pacific receives particular attention. There is also a rapidly growing focus on sustainability in shipping and in optimising container terminals.
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Optimizing picking operation in an omnichannel warehouse using simulation and automation techniques
(Sri Lanka Society of Transport and Logistics, 2023-08-26) Lakshitha, S; Kosgoda, D; Perera, HN; Gunaruwan, TL
Omnichannel retailing involves the integration of brick-and-mortar stores and online platforms, which can provide a seamless shopping experience to consumers. However, proper functions and features provided by retail alone may not suffice. Therefore, it is imperative to consider the role of the omnichannel warehouse, which offers significant features such as shorter lead time, lower cost, and larger product assortments. Our research focuses on picking operations as it is one of the primary operations in the omnichannel warehouse that consumes a high amount of time, labor, and cost. We aim to enhance the efficiency of picking operations in an omnichannel warehouse through the utilization of simulation and automation methodologies. Flexsim software was selected as the simulation tool after a thorough analysis of available methodologies. We use three modern automated technologies, conveyor belts, mobile robotic fulfillment systems, and automated guided vehicles, and identify the most appropriate picking technique for the omnichannel warehouse through a comparison of simulation models. Finally, we develop a basic framework utilizing operators for executing pickup operations and generating multiple models, incorporating automated techniques. Subsequently, a comparative analysis of all models is conducted based on each scenario’s time, distance, and cost to identify the most optimal scenario. To implement the OC concept in future studies, it should include new picking methods, operations, and sectors.
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Preventing accidents in building construction through safety management
Perera, HN; Somachandra, V; Samarasiri, NC
Building Construction sector is one of the major sectors in the construction industry in Sri Lanka. As in other sectors, building construction workers also have to face various types of hazards and accidents. Due to these accidents, there is a significant lost to the industry in terms of valuable lives, wasted time and cost overruns and these adversely affect the reputation of the construction industry. The construction includes the different specific areas such as building, road, tunnel, bridges, harbors, reservoirs etc. But, the most researchers have carried out research in the general area of construction without any separation. Further the Health and Safety of Building construction have not been covered properly by the researchers in the past. However, one of the different areas of the industry, building construction has become the most hazardous industry compared to others. This study identifies the global practices to reduce the accident probability in Building construction projects. It also identifies the accidents that frequently happen, causes for those accidents, and the impact of those accidents on the on Building Construction projects in Sri Lanka. And also from the research it is possible to investigate the applicability of globally identified best practices in Sri Lankan Building Construction Projects. The main objective of this research was to develop a guideline for Sri Lankan Building Construction projects, which would be useful in reducing accidents probability in order to minimize various losses in Sri Lanka building construction projects. Currently there is no proper research carried out regarding this issue to reduce accidents probability and minimize losses in Sri Lankan Building construction projects. Thus, this research is useful to fill that research gap in the Sri Lankan Building Construction Sector.
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A profit maximization approach for organic short food supply chains
(IEEE, 2022-07) Jayalath, MM; Perera, HN; Thibbotuwawa, A; Hettiarachchi, BD; Rathnayake, M; Adhikariwatte, V; Hemachandra, K
Demand for organic food is rapidly increasing. This is despite several constraints in the process of producing organic foods. Producers should aim to maximize their profit by catering to the rising demand of this niche market. Manufacturing cost per unit is comparatively higher in the organic chain compared to the conventional chain. Hence, producers must make critical decisions when supplying their products to different markets. A Python-based Linear Programming optimization model tested using Google optimization Tools has been developed to identify the optimum delivery volume that should be supplied to each market which has been identified in this empirical study. The designed model aims to maximize profits by minimizing unsold products and postharvest waste. The developed model can guide producers who operate in the organic perishable supply chain to gain market benefits in short food supply chains. There is a lack of research on sustainability aspects in agricultural coordination and applications in supply network performance. Therefore, this study fills this gap by addressing the issue of postharvest waste in the distribution process of organic vegetables and fruits. The model can be extended into other product variants to validate the model’s applicability under different market scenarios.
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Recalibrating retail store inventory service levels during credit card promotions
(IEEE, 2021-07) Jayasinghe, R; Perera, HN; Adhikariwatte, W; Rathnayake, M; Hemachandra, K
Cashless payment methods are growing in popularity, especially in the backdrop of the COVID19 pandemic. Credit cards are a key instrument within the cashless payment. Retail practitioners try to boost their sales by providing credit card-based promotions to customers. The tendency for customers to overspend when using credit cards is to the advantage of retailers. Retailers claim that the credit card promotions result in a sales increment of 250%. Along with the sales boost, retail stores encounter frequent stockouts and decreasing service levels. This is primarily due to the inaccurate ordering process. This paper provides a framework to set the reorder level considering the sales uplift due to credit card promotions. For the selected case scenario, the proposed framework helps to increase the retail store service level by 0.78%.
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Review of methodologies used in electricity supply and demand forecasting
(Sri Lanka Society of Transport and Logistics, 2023-08-26) Dissanayake, BI; Perera, HN; Velmanickam, L; Gunaruwan, TL
European countries began liberalizing their electricity markets to increase competition and reduce prices for consumers [1]. In a liberalized electricity market, electricity is treated as a tradable commodity like any other product. Since then, electricity markets have been subject to the same economic principles of supply and demand as other markets, with prices rising when demand outstrips supply and falling when supply exceeds demand. A variety of methods and ideas have been tried for electricity forecasting in generation, demand, and price domains over the last few decades, with varying degrees of success. Over time. Researchers have applied methodologies from time series analysis, ARIMA models to machine learning and deep learning techniques. The evolution of these techniques have improved cost reductions in the industry. The purpose of this review is to illustrate the evolution of employed methodology, the complexity of applied solutions, and the opportunities and challenges that forecasting tools offer or may encounter.
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The role of supplier switching costs and supply chain responsiveness
(Sri Lanka Society of Transport and Logistics, 2021-10) Gunarathne, GCI; Thibbotuwawa, A; Perera, HN; Gunaruwan, TL
The present study explores the impact of supplier switching costs on supply chain responsiveness in Sri Lankan Micro, Small and Medium scale (MSME) manufacturing firms considering the three categories of switching costs: procedural switching costs, financial switching costs and relational switching costs. Survey data were collected from 188 manufacturing firms and Structural Equation Modeling (SEM) was used to analyse the relationship between variables. Empirical evidence verifies that procedural switching cost is more positively related to supply chain responsiveness than the other two types of switching costs. The relational switching cost is more negatively related to supply chain responsiveness. The most important predictor that has an impact on supply chain responsiveness is relational switching cost. The result also reveals no significant relationship between financial switching costs and supply chain responsiveness. Further, the results verify that the direct relationship between supplier switching costs and supply chain responsiveness is not significant. Thus, this relationship might be influenced by different intervening variables. The findings also expose that supplier switching costs do not play a significant role in the price and product competition in the context of the manufacturing sector in Sri Lanka. Since most firms already have a thoroughly evaluated supplier base with many suppliers for the same raw materials, switching suppliers is not a major dilemma as they can be easily replaced.