Browsing by Subject "logistics"

Now showing 1 - 3 of 3

Open Access
Minimum cost path problem for Plug-in Hybrid Electric Vehicles
(Elsevier Ltd, 2015) Arslan O.; Yildiz, B.; Karaşan O.E.
We introduce a practically important and theoretically challenging problem: finding the minimum cost path for PHEVs in a road network with refueling and charging stations. We show that this problem is NP-complete and present a mixed integer quadratically constrained formulation, a discrete approximation dynamic programming heuristic, and a shortest path heuristic as solution methodologies. Practical applications of the problem in transportation and logistics, considering specifically the long-distance trips, are discussed in detail. Through extensive computational experiments, significant insights are provided. In addition to the charging infrastructure availability, a driver's stopping tolerance arises as another critical factor affecting the transportation costs. © 2015 Elsevier Ltd.
Open Access
A mobile ammunition distribution system design on the battlefield
(2010) Toyoğlu, Hünkar
Ammunition has been the most prominent factor in determining the outcome of combat. In this dissertation we study a military logistics problem in which ammunition requirements of the combat units, which are located on the battle- field, are to be satisfied in the right amount when and where they are needed. Our main objective is to provide a decision support tool that can help plan ammunition distribution on the battlefield. We demonstrate through an extensive literature review that the existing models are not capable of handling the specifics of our problem. Hence, we propose a mathematical programming model considering arc-based product-flow with O(n 4 ) decision variables and constraints. The model is a three-layer commodity-flow location routing formulation that distributes multiple products, respects hard time windows, allows demand points to be supplied by more than one vehicle or depot, and locates facilities at two different layers. We then develop a new mathematical programming model with only O(n 3 ) decision variables and constraints by considering node-based product-flow. We derive several valid inequalities to speed up the solution time of our models, illustrate the performance of the models in several realistically sized scenarios, and report encouraging results. Based on these mathematical models we propose two three-phase heuristic methods: a routing-first location-second and a location- first routing-second heuristic. The computational results show that complex real world problems can effectively be solved in reasonable times with the proposed heuristics. Finally, we introduce a dynamic model that designs the distribution system in consecutive time periods for the entire combat duration, and show how the static model can be utilized in dynamic environments.
Open Access
A two stage solution approach to spare parts distribution under a special cost structure
(2010) Koca, Esra
In this thesis, we consider a multicommodity distribution problem. We assume that there is a central depot which houses a number of different types of items. There is a finite number of geographically dispersed demand points which place orders for these items on a daily basis. The demand of these demand points should be satisfied from this central depot. We assume that a finite number of identical trucks with predetermined destinations are used for the distribution of the items from the central depot to each demand point. The demand of each demand point can be split among several trucks and a single truck is allowed to visit several demand points. Our objective is to satisfy the demand of each demand point with the minimum total distribution cost while respecting the capacity of each truck. The cost structure is dictated by the final destinations of trucks used in the distribution of the items and the set of demand points visited by each truck. We propose two different solution approaches. The first approach, called the Direct Approach, is aimed at solving the problem directly using a mixed integer linear programming formulation. Since the Direct Approach becomes computationally infeasible for real-life problems, we propose a so-called Hierarchical Approach that is aimed at solving the problem in two stages using an aggregation followed by a disaggregation scheme. We study the properties of the solutions computed with the Hierarchical Approach. We perform extensive computational studies on a data set adapted from a major automotive manufacturing company in Turkey in an attempt to compare the performances of the two approaches. Our results reveal that the Hierarchical Approach significantly outperforms the Direct Approach on the vast majority of the instances.