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A Simulated Annealing-based parallel multi-objective approach to vehicle routing problems with time windows
Authors:Raúl Baños  Julio Ortega  Consolación Gil  Antonio Fernández  Francisco de Toro
Affiliation:1. Dpt. Computer Architecture and Technology, CITIC-UGR (Research Centre on Information and Communications Technology), University of Granada, C/ Periodista Daniel Saucedo s/n, 18071 Granada, Spain;2. Dpt. Computer Architecture and Electronics, University of Almería, Carretera de Sacramento s/n, 04120 Almería, Spain;3. Dpt. Signal Theory, Telematics and Communications, CITIC-UGR (Research Centre on Information and Communications Technology), University of Granada, C/ Periodista Daniel Saucedo s/n, 18071 Granada, Spain
Abstract:The Capacitated Vehicle Routing Problem with Time Windows (VRPTW) consists in determining the routes of a given number of vehicles with identical capacity stationed at a central depot which are used to supply the demands of a set of customers within certain time windows. This is a complex multi-constrained problem with industrial, economic, and environmental implications that has been widely analyzed in the past. This paper deals with a multi-objective variant of the VRPTW that simultaneously minimizes the travelled distance and the imbalance of the routes. This imbalance is analyzed from two perspectives: the imbalance in the distances travelled by the vehicles, and the imbalance in the loads delivered by them. A multi-objective procedure based on Simulated Annealing, the Multiple Temperature Pareto Simulated Annealing (MT-PSA), is proposed in this paper to cope with these multi-objective formulations of the VRPTW. The procedure MT-PSA and an island-based parallel version of MT-PSA have been evaluated and compared with, respectively, sequential and island-based parallel implementations of SPEA2. Computational results obtained on Solomon’s benchmark problems show that the island-based parallelization produces Pareto-fronts of higher quality that those obtained by the sequential versions without increasing the computational cost, while also producing significant reduction in the runtimes while maintaining solution quality. More specifically, for the most part, our procedure MT-PSA outperforms SPEA2 in the benchmarks here considered, with respect to the solution quality and execution time.
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