Towards a Decision Making Support System for the Capacitated Vehicle Routing Problem

2013 ◽  
Vol 5 (4) ◽  
pp. 21-33 ◽  
Author(s):  
Takwa Tlili ◽  
Saoussen Krichen ◽  
Sami Faiz

Distribution of goods is of importance in logistics and supply chain management. The target of a distribution network is to specify the beneficial way for delivering goods and commodities from supply to demand points. In distribution domain, this activity can usually be viewed as a capacitated vehicle routing problem (CVRP). As the CVRP solutions remain computationally intractable, we develop in this paper an interactive routing decision making support system (R-DMSS) that integrates a swarm based approach into a geographical information system (GIS). The empirical experiments include benchmarking instances as well as a case study over the Ezzahra area in Tunisia. The R-DMSS interfaces are presented to better understand the operational aspect of the system.

Author(s):  
Fernando Francisco Sandoya Sánchez ◽  
Carmen Andrea Letamendi Lazo ◽  
Fanny Yamel Sanabria Quiñónez

This chapter presents the best-known heuristics and metaheuristics that are applied to solve the capacitated vehicle routing problem (CVRP), which is the generalization of the TSP, in which the nodes are visited by more than one route. To find out which algorithm obtains better results, there are 30 test instances used, which are grouped into 3 sets of problems according to the position of the nodes. The study begins with an economic impact analysis of the transportation sector in companies, which represents up to 20% of the final cost of the product. This case study focuses on the CVRP for its acronym capacitated vehicle routing problem, analyzing the best-known heuristics such as Clarke & Wright and sweep, and the algorithms GRASP and simulated annealing metaheuristics based.


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