Abstract
The issue of coalition formation problem has been investigated from many aspects. However, all of the previous work just take the capability of agent into account, but not consider those factors, such as the time that agent takes to achieve a task, the cost of employing agent, the credit standing of agent, the risk that the task sponsor bears, and the bias of task sponsor and so on. So we originally take these factors into account. The coalition problem in this paper is a constrained problem including a great deal of equality constraints and inequality constraints. So we adopt the death penalty function to transform it to an unconstrained one. That is to say, it becomes a single objective function. Being an unconstrained optimization algorithm, the binary particle swarm optimization algorithm is adopted to address this problem. To improve the capability of global searching of our algorithm and convergent rate of the solutions, we divide the process of coalition formation into two stages to deal with respectively. Simulations show that our algorithm is effective and feasible.
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Zheng, SF., Hu, SL., Lai, XW., Lin, CF., Su, SX. (2007). Searching for Agent Coalition Using Particle Swarm Optimization and Death Penalty Function. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2007. Lecture Notes in Computer Science, vol 4681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74171-8_20
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DOI: https://doi.org/10.1007/978-3-540-74171-8_20
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