A flipping local search genetic algorithm for the multidimensional 0-1 knapsack problem

Authors:
César L. Alonso;Fernando Caro;José Luis Montaña
Affiliations:
Centro de Inteligencia Artificial, Universidad de Oviedo, Gijón, Spain;Centro de Inteligencia Artificial, Universidad de Oviedo, Gijón, Spain;Departamento de Matemáticas, Estadística y Computación, Universidad de Cantabria
Venue:
CAEPIA'05 Proceedings of the 11th Spanish association conference on Current Topics in Artificial Intelligence
Year:
2005

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Abstract

In this paper we present an evolutionary strategy for the multidimensional 0–1 knapsack problem. Our algorithm incorporates a flipping local search process in order to locally improve the obtained individuals and also, a heuristic operator which computes problem-specific knowledge, based on the surrogate multipliers approach introduced in [12]. Experimental results show that our evolutionary algorithm is capable of obtaining high quality solutions for large size problems and that the local search procedure significatively improves the final obtained result.