Coordinating metaheuristic agents with swarm intelligence
This addresses coordination challenges in multi-agent systems for optimization problems, but it appears incremental as it builds on existing metaheuristic methods.
The paper tackled the problem of coordinating metaheuristic agents in multi-agent systems by using swarm intelligence, specifically combining simulated annealing agents with particle swarm optimization, and reported improved performance on the multidimensional knapsack problem compared to prior works.
Coordination of multi agent systems remains as a problem since there is no prominent method to completely solve this problem. Metaheuristic agents are specific implementations of multi-agent systems, which imposes working together to solve optimisation problems with metaheuristic algorithms. The idea borrowed from swarm intelligence seems working much better than those implementations suggested before. This paper reports the performance of swarms of simulated annealing agents collaborating with particle swarm optimization algorithm. The proposed approach is implemented for multidimensional knapsack problem and has resulted much better than some other works published before.