Journal
SWARM AND EVOLUTIONARY COMPUTATION
Volume 55, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.swevo.2020.100686
Keywords
Genetic algorithm; Coalition formation (CF); Ability requirement constraint; Heuristic initialization; Repair strategy
Funding
- National Outstanding Youth Talents Support Program [61822304]
- National Natural Science Foundation of China [61673058]
- NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization [U1609214]
- National Key R&D Program of China [2018YFB1308000]
- Peng Cheng Laboratory
- Beijing Advanced Innovation Center for Intelligent Robots and Systems
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In multi-agent systems (MAS), the coalition formation (CF) is an important problem focusing on allocating agents to different tasks. In this paper, three specific CF problems are considered, including the single-task single-coalition formation, the multi-task single-coalition formation, and the multi-task multi-coalition formation. The mathematical models of these three specific problems are formulated with the objective of minimizing the total cost while satisfying the ability requirement constraint. An efficient genetic algorithm with heuristic initialization and repair strategy (GAHIR) is proposed to solve the CF problem. Multiple initialization and repair methods, which utilize the prior knowledge of the specific problems, are proposed to improve the solution quality. Then, these methods are tested to prove their effectiveness. Finally, a comparison experiment about the proposed algorithm against several advanced algorithms is constructed. The results of statistical analysis by the Wilcoxon rank-sum test demonstrate that the proposed GAHIR can obtain better coalition schemes than its competitors in solving the CF problems. Furthermore, GAHIR has faster convergence speed in most instances.
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