Bee Colony Algorithm for the Multidimensional Knapsack Problem.

In this paper we present a new algorithm based on the Bee Colony Optimization (BCO) meta-heuristic for the Multidimensional Knapsack Problem (MKP), the goal of which is to find a subset of objects that maximizes a given objective function while satisfying some resource constraints. We show that our new algorithm obtains better results than Ant Colony Optimization algorithms and on most instances it reaches best known solutions. Especially we propose an efficient algorithm to produce randomly new solutions. [ABSTRACT FROM AUTHOR]