A vehicle routing problem solved by using a hybrid genetic algorithm

Authors:
Geonwook Jeon;Herman R. Leep;Jae Young Shim
Affiliations:
Department of Operations Research, Korea National Defense University, Seoul 122-875, Republic of Korea;Department of Industrial Engineering, University of Louisville, Louisville, KY 40292, USA;Transportation Staff, The 26th Division, Korea Army, Yangju 482-839, Republic of Korea
Venue:
Computers and Industrial Engineering
Year:
2007

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Abstract

The main purpose of this study is to find out the best solution of the vehicle routing problem simultaneously considering heterogeneous vehicles, double trips, and multiple depots by using a hybrid genetic algorithm. This study suggested a mathematical programming model with a new numerical formula which presents the amount of delivery and sub-tour elimination. This model gives an optimal solution by using OPL-STUDIO(ILOG CPLEX). This study also suggests a hybrid genetic algorithm (HGA) which considers the improvement of generation for an initial solution, three different heuristic processes, and a float mutation rate for escaping from the local solution in order to find the best solution. The suggested HGA is also compared with the results of a general genetic algorithm and existing problems suggested by Eilon and Fisher. We found better solutions rather than the existing genetic algorithms.