Journal
APPLIED INTELLIGENCE
Volume 44, Issue 3, Pages 665-686Publisher
SPRINGER
DOI: 10.1007/s10489-015-0718-2
Keywords
Group Mosquito Host-Seeking Model (GMHSM) and algorithm (GMHSA); Leader decision; Traveling Salesman Problem (TSP); 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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The host-seeking behavior of mosquitoes is very interesting. This paper is motivated by the following general observation on mosquito groups and their host-seeking behavior in nature: (1) Mosquitoes' behavior has possession of the parallelism, openness, local interactivity and self-organization. (2) Mosquito groups seek host very fast. (3) The host-seeking behavior is similar to the producer-scrounger process, which assumes that group members search either for finding (producer) or for joining (scrounger) opportunities. It stimulates us to extend a mosquito system model in nature to group mosquito host-seeking model (GMHSM) and algorithm (GMHSA) for intelligent computing. In this paper, we propose GMHS approach and show how to use it. By GMHSM, the TSP is transformed into the kinematics and dynamics of mosquito groups host-seeking process. The properties of GMHSM and GMHSA, including the correctness, convergence and stability, have been discussed in this paper. The GMHS approach has many advantages in terms of multiple objective optimization, large-scale distributed parallel optimization, effectiveness of problem-solving and suitability for complex environment. Via simulations, we test the GMHS approach and compare it with other state-of-art algorithms.
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