Journal
INFORMATION SCIENCES
Volume 233, Issue -, Pages 87-108Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2012.12.053
Keywords
Traveling salesman problem (TSP); Mosquito host-seeking algorithm (MHSA); Distributed and parallel algorithm
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Funding
- National Natural Science Foundation of China [60905043, 61073107, 61173048]
- Innovation Program of Shanghai Municipal Education Commission
- Fundamental Research Funds for the Central Universities
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This paper proposes a new nature-inspired algorithm (NA)-mosquito host-seeking algorithm (MHSA)-the inspiration for which comes from the host-seeking behavior of mosquitoes. Applying the algorithm to the traveling salesman problem (TSP), every city pair is treated as an artificial mosquito, and the TSP solving process is transformed into the host-seeking behavior of a swarm of artificial mosquitoes. We study the evolution of swarms, the artificial mosquitoes' microcosmic actions, and macroscopic swarm intelligence, and present efficient solutions to TSP using MHSA. The proposed MHSA is fundamentally different from the other popular NAs in its motivation, principle, the optimization mechanism, its elements and their states, and the biological model, the mathematical model and theoretical foundation on which it is based. We show that (1) MHSA can converge; (2) its parameter setting does not depend on algorithm learning or prior knowledge; and (3) MHSA can describe complex behaviors and dynamics. The properties of MHSA, including correctness, convergence and stability, are discussed in details. Simulation results attest to the effectiveness and suitability of MHSA. (c) 2013 Elsevier Inc. All rights reserved.
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