Abstract
In this paper we examine five different strategies for limiting the local search neighborhoods in the context of vehicle routing problems. The vehicle routing problem deals with the assignment of a set of transportation orders to a fleet of vehicles, and the sequencing of stops for each vehicle to minimize transportation costs. The examined strategies are applied to three standard neighborhoods and implemented in a recently suggested powerful memetic algorithm. Experimental results on 26 well-known benchmark problems indicate significant speedups of almost 80% without worsening the solution quality. On the contrary, in 12 cases new best solutions were obtained.
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Nagata, Y., Bräysy, O. (2008). Efficient Local Search Limitation Strategies for Vehicle Routing Problems. In: van Hemert, J., Cotta, C. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2008. Lecture Notes in Computer Science, vol 4972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78604-7_5
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DOI: https://doi.org/10.1007/978-3-540-78604-7_5
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