International Research Symposium on Pure and Applied Sciences (IRSPAS)
Permanent URI for this communityhttp://repository.kln.ac.lk/handle/123456789/15650
Browse
3 results
Search Results
Item 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 demandsItem 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 simulationItem 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.