A Multi-Agent based Hyper-Heuristic Algorithm for the Winner Determination Problem

In this paper, we propose a Multi-Agent based Hyper-Heuristic algorithm for the Winner Determination Problem named MAH2-WDP. This algorithm explores a set of cooperating agents to select the appropriate operation using learning techniques. MAH2-WDP is specialized for local search methods and evolutionary methods where the following agents are seeking to improve the search within reinforcement learning: the mediator agent, two local search agents, the perturbation agent and two recombination agents. Our computational study shows that the proposed algorithm performs well on the tested benchmark instances in terms of solution quality.