Genetic Algorithm Based Combinatorial Auction Method for Multi-Robot Task Allocation |
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Authors: | GONG Jian-wei HUANG Wan-ning XIONG Guang-ming and MAN Yi-ming |
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Affiliation: | School of Mechanical and Vehicular Engineering, Beijing Institute of Technology, Beijing 100081, China |
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Abstract: | An improved genetic algorithm is proposed to solve the problem of bad real-time performance or inability to get a global optimal/better solution when applying single-item auction (SIA) method or combinatorial auction method to multi-robot task allocation.The genetic algorithm based combinatorial auction (GACA) method which combines the basic-genetic algorithm with a new concept of ringed chromosome is used to solve the winner determination problem (WDP) of combinatorial auction.The simulation experiments are conducted in OpenSim, a multi-robot simulator.The results show that GACA can get a satisfying solution in a reasonable shot time, and compared with SIA or parthenogenesis algorithm combinatorial auction (PGACA) method, it is the simplest and has higher search efficiency, also, GACA can get a global better/optimal solution and satisfy the high real-time requirement of multi-robot task allocation. |
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Keywords: | multi-robot task allocation combinatorial auctions genetic algorithm |
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