Multiple Objective Genetic Local Search Algorithm

The paper presents a multiple objective genetic local search algorithm for multiple objective combinatorial optimization. The algorithm hybridizes recombination operators with local improvement heuristics. In each iteration of the algorithm a scalarizing function is drawn at random. Then, two solutions being good on the current scalarizing function are recombined and a local improvement heuristic is applied to the offspring. The paper describes also results of an experiment on the multiple objective 0/1 knapsack problem with multiple knapsack constraints.