Browsing by Author "Niwunhella, D. H. H."

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Analyzing Factors that Impact on Performance of Pickers in Third-Party Logistics Warehouses in Sri Lanka
(Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka, 2022) Prasadika, A. P. K. J.; Wijayanayake, A. N.; Niwunhella, D. H. H.
Order picking is the most crucial and expensive operation in a warehouse which affects customer satisfaction and the profitability of the warehouse. Picker is the employee who is responsible for the order picking process. So, picker performance is very important in improving the overall performance of the warehouse. Therefore, identifying the factors that have an impact on the performance of the pickers is advantageous. The main objective of this research is to identify the relationship between factors that has an impact on picker and picker performance through the Partial Linear Square – Structural Equation Modelling (PLS-SEM) technique using SmartPLS software. Initially, the most important twelve factors were identified by reviewing the past literature and industry experts’ opinions. They were divided into three main categories based on the characteristics and to reduce the complexity of the model which are picker-related factors, management-related factors, and warehouse-related factors. The data analysis was done in two steps to discover direct and moderator relationships, separately. The product type that the pickers handle is the moderator used in this study. The results of the PLS-SEM analysis show that picker-related factors and warehouse-related factors have a significant impact on picker performance at the significance level of 0.05, while management-related factors have a significant effect on picker performance at the significance level of 0.10. Further, the product type moderates all three relationships. The outcomes of the study help the managers of the warehouses to improve the performance of the pickers so that the overall performance of the warehouse can be improved.
Cluster-based Transportation Optimization – A Case Study from Pharmaceutical Supply Chains (PSC).
(In: Proceedings of the International Postgraduate Research Conference 2017 (IPRC – 2017), Faculty of Graduate Studies, University of Kelaniya, Sri Lanka., 2017) Niwunhella, D. H. H.; Rupasinghe, T.D.
Transportation planning attempts to allocate fixed logistics capacity in the best possible way, for particular business requirements. This study focuses on the pharmaceutical supply chains, as optimization of medicine distribution routes has become an urgent issue that needs to be solved. The cost components of many distribution and transportation systems represent the routing and scheduling of vehicles, but there are only a few optimization approaches that have been introduced to effectively solve Vehicle Routing Problem (VRP). Therefore, this study presents a simulation based solution approach for transportation optimization, in order to minimize the cost, based on the pre-identified pharmaceutical product clusters. The simulation models are developed using the SupplyChainGuru® modelling and simulation platform, where vehicle routing models are developed to simulate the inherent features of the product families using test cases from the literature and the benchmark instances listed on the repository of CVRPLib. The study proposes and models five product characteristic-based clusters namely, time sensitive pharmaceuticals, hazardous pharmaceuticals, hybrid pharmaceuticals, condition constrained pharmaceuticals (conditions such as pressure/temperature, etc.), and general pharmaceuticals. The baseline VRP model is compared with the cluster specific VRP models developed for each product cluster. The results of the study depict that the total transportation cost minimizes as the products are routed with respect to the inherent product clusters, than the cost of routing without considering cluster-specific characteristics. The maximum percentage cost reduction is for the general/condition constrained cluster (64.04%), whereas the minimum is for the time sensitive product cluster (0.59%). This product clustering approach of transportation optimization could be utilized dynamically to provide efficient delivery of products to the consumers, and could be adopted in related industrial supply chains.
An Effective Lateral Transhipment Model for A Multi-Location Inventory Setting to Minimize
(Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka, 2022) Kumari, A.G.K.C.; Wijayanayake, A. N.; Niwunhella, D. H. H.
Managing inventory levels to ensure on-shelf availability of products is a challenge that retailers face on a daily basis. Even though it is desirable to have additional inventory to ensure the availability of products, it increases the inventory holding cost. Hence, retailers use lateral transhipment as a method to redistribute inventory from a location which has excess inventory to another outlet which faces / will face stockouts. This paper proposes a mathematical model to minimize the total cost through proactive lateral transhipment while reducing the stockouts, significantly. A multi-item, multi-location inventory system was considered, and a cost minimization model was developed based on the tradeoff between the potential gain and the transhipment cost. The model was implemented using Python programming language and validated using a real-world data set from one of the leading supermarket chains. The results from the model have shown that it can reduce the total cost and stockout occurrences significantly.
Framework for Measuring Sustainability Performance of Logistics Service Providers- A Systematic Review of Literature
(Faculty of Commerce and Management Studies University of Kelaniya, Sri Lanka, 2020) Prabodhika, A. P. K. J.; Niwunhella, D. H. H.; Wijayanayake, A
Sustainability and sustainable development have become a buzzing topic in today's business world. Business organizations are more inclined towards making themselves economically, socially, and environmentally more sustainable. With the introduction of concepts like “Sustainable Supply Chain Management” organizations have determined to not only make themselves sustainable but to make the whole supply chain sustainable as well. As part of the supply chain, Logistics Service Providers (LSPs) are no exception. With the pressure from the internal and external stakeholders such as Government, Non- Government Organizations (NGOs), public authorities, LSPs are more inclined towards making themselves more sustainable and ‘being sustainable’ has become a competitive advantage for them now. To measure and evaluate the sustainability performance, various frameworks and standards have been introduced. This paper reviews the available literature from 2010 to 2019 under logistics service providers, sustainability, and sustainability performance evaluation. This study was conducted through a systematic review of the literature and presents various sustainability indicators used by researchers, sustainability performance evaluation models, and frameworks and the approaches used by researchers in developing those models and frameworks for the logistics service providers and the supply chain as a whole. The review brings up the importance of further analyzing and testing those proposed models and frameworks using case studies and the need for incorporating opinions of stakeholders when developing the models for the evaluation of sustainability performance and frameworks.
Meta Heuristic Approach to Optimize Airline Fleet Re-Assignment
(International Postgraduate Research Conference 2019, Faculty of Graduate Studies, University of Kelaniya, Sri Lanka, 2019) Fernando, P.A.; Niwunhella, D. H. H.; Nanayakkara, L.D.J.F.
Disruptive situations occur very often in airline environments where daily operational plans related to airline fleet deviate from the original schedules due to unanticipated circumstances, particularly as airlines operate in extremely uncertain and cost intensive environments. The frequency and cost associated with disruptions affect airline profitability to a great extent. In a disrupted state, it is needed by the airline to dynamically change fleet schedules; re-assign fleet to stabilize operational continuity. The research aims at developing a model based on meta-heuristics for the formal optimization of disruption recovery decisions. The mathematical model proposed, has the objective of recovering the disrupted flight(s) with minimum deviation from the original schedule, minimizing the total cost of disruption management. When deciding on the recovery action, the best suited option that implies the lowest cost must be chosen. In order to achieve this, flights can be swapped, delayed, cancelled or its passengers could be rerouted using a flight offered by the same airline or a different airline. The costs of different recovery strategies such as delaying, cancelling, swapping and passenger rerouting are therefore included in the objective function of the model. Costs related to passengers are incorporated to the cost calculations of each of the recovery strategies. The constraints involved in the model support consistent operations in a practical airline environment and are related to aircraft, airports, itineraries, turn-round times, configuration of aircrafts and maintenance. Variables in the model could be categorized as input data and cost coefficients, strategic decision variables and computed output variables and cost factors which will be reported from the optimization process. Variables and constraints in the proposed model were identified through a thorough survey of literature and interviews conducted with airline operations control personnel to gather and cross validate the industrial acceptability of the propositions and to identify possible revisions. Solving one disruption has a downstream impact on the entire airline operations plan and may require changes to be made in the overall operational schedule subsequent to the recovery of one disruption. This is solved using a metaheuristic algorithm based on tabu search, where the optimum way of adjusting the rest of the flight schedule is found. The study identifies and validates the heuristics involved in the current procedure followed in aircraft schedule recovery and the rational/logic behind the process practiced, that can support the optimization of disruption recovery decisions.
A MILP model to optimize the proportion of production quantities considering the ANP composite performance index
(Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka, 2021) Thalagahage, N. T. H.; Wijayanayake, A. N.; Niwunhella, D. H. H.
The apparel industry is considered as one of the most labor-intensive industries where Production Planning and Control (PPC) is considered as an important function, because of its involvement from scheduling each task in the process to the delivery of customer demand. Line planning is a sub-process within PPC, through which the production orders are allocated to production lines according to their setting and due dates of production completion. The decisions that address line planning functions still heavily rely on the expertise of the production planner. When production planners are required to select production lines for the production of a particular type of product, little emphasis has been placed on ways to apportion certain production orders to the most appropriate production system. In this research, a framework is developed using Analytical Network Process (ANP) which is a Multi-Criteria Decision Making (MCDM) method, enabling the incorporation of all the planning criteria in the selection of a production line. The weighted scores obtained by the best alternative production lines are used in a Linear Programming model to optimize the resource allocation in an apparel firm.
Model to optimize the quantities of delivery products prioritizing the sustainability performance
(Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka, 2021) Prabodhika, A. P. K. J.; Niwunhella, D. H. H.; Wijayanayake, A. N.
Many manufacturers and retailers often outsource their logistics functions to Logistics Service Providers (LSPs) to focus more on their core business process. Due to the competitiveness and the popularity of the sustainability concept, those organizations evaluate their prospective LSPs not only based on economic aspects like cost, service quality but also on social and environmental aspects as well when selecting LSPs. This paper proposes a methodology that can be used by organizations when evaluating and selecting LSPs based on their sustainability performance. Analytic Network Process (ANP) is used in evaluating the LSPs’ sustainable performance since multiple dimensions and indicators need to be incorporated when measuring the sustainability performance. A Linear Programming Problem (LPP) model was proposed which allows the organizations to decide both desired number of LSPs and the volume to be allocated for those selected LSPs. The proposed methodology is flexible as it depends on the sustainability requirements of the organization when selecting LSPs. Both the indicators and their relative importance are up to the organization to decide.
Optimizing the process of airline fleet re-assignment to minimize the impact of disruptions
(4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Fernando, P. A.; Nanayakkara, L. D. J. F.; Tharaka, V. K.; Niwunhella, D. H. H.
Aircraft assignments often deviate from the original schedule due to technical failures, operational requirements and other unforeseen circumstances which can be termed as disruptions. In such situations, it is necessary for the airline to assign an aircraft on ground to replace the grounded aircraft. Such reassignments entail re-work of the network, seat configurations, fuel requirements, load and other operational requirements. An efficient method to carry out re-assignments is absent in the Sri Lankan context; although research has been conducted to identify the optimum methodology for fleet assignment, those related to disruption management and aircraft re-assignment to minimize the impact of disruptions are scarce; disruptions still cost about 10% of airline revenue according to research conducted. Through the background study on Sri Lankan Airlines and literature, it was identified that the constraints of existing models do not capture all the elements such as passengers, aircraft and crew in the optimization of their objective functions. Available models do not consider re-assignment options such as ferrying, swapping, delaying and cancelling, in their entirety either. The exploratory study established the fact that disruption recovery is a time consuming and complex task which is required to be planned and executed in a matter of minutes. The controllers are often constrained to produce only a single feasible plan of action which may not be optimal. It is a difficult task to evaluate the quality of the recovery action which is to be executed. In most airlines, the personnel generating the recovery plan do not have adequate software-based decision support to construct high-quality recovery options, to compare available options or assess the down-stream impact of a disruption. The research is aimed at developing a model based on heuristics and meta-heuristics for supporting a model for the formal optimization of disruption recovery decisions. The impact of disruptions on the airline, types of fleet, nature of assignments, past assignments and requirements of an assignment are taken into consideration as qualitative data analysis. Quantitative data analysis is used to assess alternative assignments that could have been possible, comparison of options, model building and impact analysis in terms of cost and frequency. The study identified and validated the heuristics/meta-heuristics involved in the current methodology followed in aircraft schedule recovery and the rational/logic behind current process that can support optimization model building using heuristics, integer programming and simulation
A simulation modelling approach for vehicle routing problem in cluster-based pharmaceutical supply chains.
(International Research Symposium on Pure and Applied Sciences, 2017 Faculty of Science, University of Kelaniya, Sri Lanka., 2017) Niwunhella, D. H. H.; Rupasinghe, T. D.
Pharmaceuticals directly affect the health conditions of millions of people. It is important to find the most effective and optimized methods for pharmaceutical supply chains to provide a better quality product from manufacturers to the end-consumer. The supply chain process of the pharmaceutical products, when compared with the other commercial goods and services, is given higher priority since it costs high amount of money and time to produce and deliver pharmaceutical products, since the process is not well-managed. Furthermore, all the contributors in the pharmaceutical domain go through specific rules and regulations, uncertainty in demand, constraints such as biological factors in the process. In recent years, with the continuous improvement of the medical service level and technical level, people’s demand for drugs significantly improved year by year. Therefore, it is vital that the delivery of pharmaceutical products is conducted effectively and efficiently. In addition to quality, the routing and scheduling of vehicles represent an important component of many distribution and transportation systems’ costs. With the computational constraints of solving Vehicle Routing Problem (VRP) which is NP-hard, a few optimization and approximation approaches have been introduced to successfully solve VRPs in the recent past. Thus, this study depicts a vehicle routing optimization with the objective of minimizing the cost based on the pharmaceutical product clusters using a simulation-based solution approach using SupplyChainGuru® modelling and simulation tool. Vehicle routing models are developed to simulate the pre-identified clusters (product families) using test cases from the literature and the benchmark instances listed on the repository of CVRPLib. Then the behavior and the nature of vehicle routing in pre-defined product clusters are identified and modelled via varying wide variety of variables. The baseline model is compared with the scenarios of each product cluster and the most optimized vehicle routing model will be identified and validated through simulation. The study concluded that the overall cost is minimized, when the pharmaceuticals are routed to better suit their product characteristics, rather than distributing the products without considering the inherent product characteristics, which are dynamically modelled and evaluated to provide better quality products to the patients. This product clustering-based simulation of VRP will indeed optimize the VRP in Pharmaceutical Supply Chains and will provide the platform to extend the cluster based optimization to related industries as well.
Simulation-Based Efficiency Assessment of Integrated First-Mile Pickup and Last-Mile Delivery in an E-Commerce Logistics Network
(Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka, 2022) Ranathunga, M. I. D.; Wijayanayake, A. N.; Niwunhella, D. H. H.
Logistics operations are crucial in the e-commerce supply chain as they deal with high costs as well as they have a significant environmental impact. The first-mile and last-mile delivery operations in e-commerce logistics are regarded as the operations with the highest costs. As a result, e-commerce service providers are keen to improve their first mile and last-mile delivery processes. Therefore, this study has been conducted to optimize transportation cost and distance of combined first-mile pickup and last-mile delivery operations while meeting some practical requirements such as a variety of package types, package compatibility on different types of vehicles, and a heterogeneous fleet of vehicles. After a careful literature review, this paper introduces a mathematical model to optimize the simultaneous first-mile pickup and last-mile delivery. The proposed mathematical model was simulated in SupplyChainGuru® modelling and simulation software. The study concluded that when first-mile pickup and last-mile delivery are routed simultaneously, rather than distributing and collecting the products as two separate operations, the overall cost is minimized by about 34%, and the distance is reduced by about 42% while reducing the number of vehicles on the route and utilising the maximum possible capacity of vehicles. This simultaneous pickup and delivery will improve the routing of the e-commerce logistic supply chain and will serve as a platform for extending the simultaneous pickup and delivery process to other industries as well.
Solution approach to incompatibility of products in a multi-product and heterogeneous vehicle routing problem: An application in the 3PL industry
(Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka, 2021) Weerakkody, H. D. W.; Niwunhella, D. H. H.; Wijayanayake, A. N.
Vehicle Routing Problem (VRP) is an extensively discussed area under supply chain literature, though it has variety of applications. Multi-product related VRP considers about optimizing the routes of vehicles distributing multiple commodities. Domestic distribution of goods of multiple clients from a third-party logistics distribution center (DC) is one example of such an application. Compatibility of products is a major factor taken into consideration when consolidating and distributing multiple products in the same vehicle. From the literature, it was identified that, though compatibility is a major consideration, it has not been considered in the literature when developing vehicle routing models. Therefore, this study has been carried out with the objective of minimizing the cost of distribution in the multi-product VRP while considering the compatibility of the products distributed, using heterogeneous vehicle types. The extended mathematical model proposed has been validated using data obtained from a leading 3PL firm in Sri Lanka which has been simulated using the Supply Chain Guru software. The numerical results showcase that cost has been reduced when consolidating shipments in a 3PL DC. The study will contribute to literature with the finding that the compatibility factor of products can be considered when developing vehicle routing models for the multi-product related VRP.
Solution approaches for combining first-mile pickup and last-mile delivery in an e-commerce logistic network: A systematic literature review
(Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka, 2021) Ranathunga, M. I. D.; Wijayanayake, A. N.; Niwunhella, D. H. H.
Logistics is one of the primary areas of operation within cutting-edge supply chain operations. In the e-commerce supply chain also logistics operations play a vital part. The logistics operations must be controlled effectively and efficiently since they deal with the high-cost besides environmental impacts. In e-commerce logistics operations, first-mile and last-mile delivery operations are considered as the operations with the highest costs incurred. So, e-commerce service providers are interested in optimizing their first-mile and last-mile delivery operations. Though it is known that the integration of first-mile pickup and last-mile deliveries will minimize the cost of transportation, there are more practical concerns to be taken into account when combining the first-mile pickup and last-mile delivery operations. Capacitated Vehicle Routing Problem (CVRP) is discussed in the literature as a solution approach for this kind of problems. The objective of this study is to provide a comprehensive overview of the current CVRP related literature, including models, algorithmic solution approaches, objectives, and industrial applications, with a focus of identifying interesting study paths for the future to improve distribution in e-commerce logistics networks by combining first-mile pickup and last-mile delivery operations. The findings of the study have demonstrated that constraints and features of Vehicle Routing Problem with Backhauls are very attractive with today's e-commerce operations, and the majority of the cited publications employed approximation methods rather than precise algorithms to solve these types of models.
Vehicle routing optimization in Sri Lankan megacity logistics context
(4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Warnakulasuriya, M. M.; Vidanagamachchi, K.; Niwunhella, D. H. H.; Nanayakkara, L. D. J. F.
Sri Lanka has been making its way to develop its metropolitan city, Colombo, as a megacity. Transportation is one of the basic components to consider in planning any city emerging as megacities. City logistics function is a major factor which influences the economy and the social activities of a country. In megacity logistics, the growth in the volume of freight traffic and the aim to optimize the logistics activities have led research in recent years. According to the National Transport Report for year 2017, Port of Colombo handled 651,968 of Imports (TEUs) alone in year 2016. The majority of the destinations of this freight is Colombo and its suburbs. Considering the growing demands, the Western Region Megapolis Master Plan has been developed to cater systematic inland freight transportation in Colombo and suburbs. Therefore, it is important to focus on optimizing the urban transport network as well as the freight transport which has been given insignificant attention to date. Routing of flows and scheduling of deliveries are the two main factors to be considered in optimizing freight transport on which a lot of opportunities lie upon. Routing of flows is the pattern of flow at different spatial scales and scheduling of deliveries determines the flow of freight traffic through time windows. This study investigates the impact of city logistics for the road network in Sri Lanka, considering the main land transport corridors to map the freight flows as identified in the Megapolis Master Plan – Sri Lanka. This is done through a systematic data collection from a company handling freights within Colombo to match the Sri Lankan city logistic scenario about the freight transport regarding the units that are transported, and travel times taken for the considered destinations from the depot where freights are consolidated before released into the road network. It also identifies main city destinations around Colombo, the freight flows and freight volumes (in TEUs) in determining the impact of it for the road network. Thereby, this study will depict a vehicle routing optimization model to optimize the freight outflow function, minimizing the time taken. This is conducted through a simulation-based approach using the Supply Chain Guru simulation and modelling software, which is tested with the data collected. This vehicle routing simulation will provide platform for improved operation with identified demands to minimize the freight traffic and decision making in terms of the road network utilization for future demands