Honey Bees Mating Optimization algorithm for large scale vehicle routing problems |
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Authors: | Yannis Marinakis Magdalene Marinaki Georgios Dounias |
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Affiliation: | (1) Decision Support Systems Laboratory, Department of Production Engineering and Management, Technical University of Crete, University Campus, 73100 Chania, Crete, Greece;(2) Industrial Systems Control Laboratory, Department of Production Engineering and Management, Technical University of Crete, University Campus, 73100 Chania, Crete, Greece;(3) Department of Financial and Management Engineering, Management and Decision Engineering Laboratory, University of the Aegean, 31 Fostini Str., 82100 Chios, Greece |
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Abstract: | Honey Bees Mating Optimization algorithm is a relatively new nature inspired algorithm. In this paper, this nature inspired
algorithm is used in a hybrid scheme with other metaheuristic algorithms for successfully solving the Vehicle Routing Problem.
More precisely, the proposed algorithm for the solution of the Vehicle Routing Problem, the Honey Bees Mating Optimization
(HBMOVRP), combines a Honey Bees Mating Optimization (HBMO) algorithm with the Multiple Phase Neighborhood Search–Greedy Randomized
Adaptive Search Procedure (MPNS–GRASP) and the Expanding Neighborhood Search (ENS) algorithm. Besides these two procedures,
the proposed algorithm has, also, two additional main innovative features compared to other Honey Bees Mating Optimization
algorithms concerning the crossover operator and the workers. Two sets of benchmark instances are used in order to test the
proposed algorithm. The results obtained for both sets are very satisfactory. More specifically, in the fourteen classic instances
proposed by Christofides, the average quality is 0.029% and in the second set with the twenty large scale vehicle routing
problems the average quality is 0.40%. |
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