A Flipping Local Search Genetic Algorithm for the Multidimensional 0-1 Knapsack Problem.

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. Keywords: Evolutionary computation, genetic algorithms, knapsack problem, linear 0-1 integer programming. [ABSTRACT FROM AUTHOR]