A Cooperative Swarm Optimization-Based Algorithm for the Quadratic Multiple Knapsack Problem

The knapsack problem arises in real world applications, like transportation, manufacturing systems, finance, and supply chain management. In this paper, we investigate the use of a cooperative particle swarm optimization for solving the quadratic multiple knapsack problem. The standard swarm optimization is reenforced by using a local search procedure, where the swapping operator is introduced that combines items belonging to different bins (knapsacks) according to their critical items. The performance of the method is evaluated on benchmark instances of the literature, where its results are compared to the best available bounds available in the literature.