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Energy redistribution in autonomous hybridization of agent-based computing

Godzik Mateusz

Computer Science

2021

T. 22 (3)

345–365

Evolutionary multi-agent systems (EMAS) are very good at dealing with diffi cult, multi-dimensional problems. Research is currently underway to improve this algorithm, giving agents even more freedom not only to solve the problem, but also to make decisions about the behavior of the algorithm. One way is to hybridize this algorithm with other existing algorithms to create the Hybrid Evolutionary Multi Agent-System (HEMAS). Unfortunately, such connections generate problems in the form of unbalanced agent energy levels. One solution is to use an agent energy redistribution operator. The article presents three different proposals for such redistribution operators, compared them with each other and selected the best based on the results of numerous experiments.

An adaptive hybrid metaheuristic for permutation flowshop scheduling

Moccellin J., Santos M.

Control and Cybernetics

2000

Vol. 29, no 3

761-771

In this paper we present a hybrid Tabu Search - Simulated Annealing heuristic fox the minimal makespan flowshop sequencing problem. In order to evaluate the effectiveness of the hybridization we compare the hybrid metaheuristic with pure Tabu Search and Simulated Annealing heuristics. The results from computational experience are discussed.