Browsing by Author "Edirisinghe, PM"

Now showing 1 - 4 of 4

item: Conference-Full-text
A capacitated vehicle routing problem model for stationery industry
(IEEE, 2022-07) Liyanage, RN; Thibbotuwawa, A; Edirisinghe, PM; Rathnayake, M; Adhikariwatte, V; Hemachandra, K
This paper aims to present an optimization solution for the distribution of stationery products with a seasonal demand pattern. The problem is structured as the capacitated vehicle routing problem is one-to-many with multiple products, where each customer has a variety of product types and demands. It is observed that yearly distance has varied by 43% between the season and off-season periods and the total distance savings throughout the year is around 40%. A mixed-integer linear programming model was used to give an optimal solution and the Gurobi solver was used to arrive at the solution. The objective of the research is to determine the appropriate number of vehicles used to complete the delivery process in both seasonal and off-seasonal periods, together with the route sequence of every vehicle, such that the distance-related costs are minimized with effective vehicle capacity utilization.
item: Article-Full-text
Confidence limits for compliance testing using mixed acceptance criteria
(2020) Edirisinghe, PM; Mathew, T; Peiris, TSG
For manufactured items sold by weight or volume, this article considers mixed acceptance criteria that put limits on the sample mean or on an upper confidence limit based on the sample mean and on the number of individual sample units that are nonconforming. For a normally distributed quality characteristic of interest, this article develops lower confidence limits for the mixed acceptance criteria applying the concept of a generalized pivotal quantity and applying a bias-corrected and accelerated parametric bootstrap. The accuracy of the confidence limits is assessed using estimated coverage probabilities, and the results are illustrated with an example.
item: Thesis-Full-text
Development of a mobile cash acceptance model: structural equation approach
Bandara, AMASM; Edirisinghe, PM
Development of a mobile cash acceptance model: structural equation approach This study intends to develop a conceptual model integrating the dimensions of mobile service quality (MSQ) in to other determinants of usage intension (UI) of Mobile Cash (MC) services using Partial Least Square – Structural Equation Modeling (PLS-SEM). The Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) has been selected as the theoretical base for the study. Considering both functional and technical quality aspects of MSQ, seven dimensions have been used (Reliability (REL), Responsiveness (RES), Assurance (ASU), Empathy (EMP), Tangibles (TAN), Convenience (CON), and Customer Perceived Network Quality (NQT)). A survey was carried out in a Higher Education Institute with a sample of 272 MC users. The measurement model assessment has revealed an adequate level of reliability, and validity in the measurement instrument. Therefore, eight different models have been formulated and tested using PLS-SEM to identify a statistically significant model. The standardized root mean square residual (SRMR) used as the determinant of model goodness of fit and bootstrapping procedures were used to determine the significant paths within each model. Based on the indications of the Recommended model, it was concluded that only five UTAUT2 variables (Performance Expectancy, Social Influence, Facilitating Conditions, Price Value and Habit) have direct effects (p<0.05) on UI and only the six dimensions that represent the functional quality aspect of MSQ (RES, ASU, CON, TAN, EMP and REL) have shown significant indirect effects (p<0.05) on UI where RES alone showed a negative effect. Since the technical quality dimension (NQT) did not show any significant effect on UI, the service providers are recommended to pay more attention on the functional quality rather than technical quality to improve future usage of Mobile cash services.
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