Abstract
This paper introduces a new heuristic method to solve the location-routing problem (LRP). Facility location problem (FLP) and vehicle routing problem (VRP) are considered simultaneously in the LRP. The problem selects the location of depot(s) to be established among a set of potential sites. On the other hand, the allocation of customers to depot(s), and the distribution routes between the customers and depot(s) are decided, too. In this paper, capacitated LRP (CLRP) is considered, in which the vehicles and the depots have a predefined capacity to serve the customers. A greedy clustering method (GCM-LRP) in four phases is proposed. The method clusters the customers using a greedy search algorithm, selects the most appropriate location of depot(s), allocates the clusters to the depot(s), and finally sets routes between the depot(s) and customers using ant colony system (ACS). The numerical experiments on a set of benchmark instances show the efficiency of the proposed method. Key words: Capacitated location-routing problem, greedy clustering method, greedy search algorithm, ant colony system.
Highlights
Ever increasing demand of customers for less waiting time to receive their desired products, and competitive prices between the producers, make logistics the main problem in supply chain management
The solutions obtained by Simulated Annealing (SA)-ant colony system (ACS) (Bouhafs et al, 2006), GRASP (Prins et al, 2006), LRGTS (Prins et al, 2007), the clustering based heuristic (CH) (Barreto et al, 2007) and HybPSO-location-routing problem (LRP) (Marinakis and Marinaki, 2008b) are shown in columns 4 to 8
A new heuristic method for the capacitated locationrouting problem is presented in this paper
Summary
Ever increasing demand of customers for less waiting time to receive their desired products, and competitive prices between the producers, make logistics the main problem in supply chain management. The LRP is defined as a facility location problem (FLP) that solves the vehicle routing problem (VRP), simultaneously. In capacitated LRP (CLRP), the problem is constrained with the vehicles and the depot(s) capacities to supply the customers. The unitary cost of distribution system and the capacity of the vehicles are considered in solving the problem too. The objectives are to determine the location of depots, and a set of customers to be served by each depot as well as the distribution routes. This paper proposes a greedy clustering method (GCM-LRP) to solve the CLRP. The third step allocates the clusters to depots, and ant colony system (ACS) is applied to set up the best routes between the depot(s) and the assigned customers
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
