Abstract
We propose a general solution method framework based on a Collaborative Agent Teams (CAT) architecture to tackle large-scale mixed-integer optimization problems with complex structures. This framework introduces several conceptual improvements over previous agent teams’ approaches. We discuss how to configure the three key components of a CAT solver for multidimensional optimization problems: the problem representation, the design of agents, and the information sharing mechanisms between agents. Implementation guidelines are also given.
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Carle, MA., Martel, A., Zufferey, N. (2018). Collaborative Agent Teams (CAT): From the Paradigm to Implementation Guidelines. In: Korošec, P., Melab, N., Talbi, EG. (eds) Bioinspired Optimization Methods and Their Applications. BIOMA 2018. Lecture Notes in Computer Science(), vol 10835. Springer, Cham. https://doi.org/10.1007/978-3-319-91641-5_6
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