Multi-Agent Collaborative Research Based on an Optimization Method about Multiple Evaluation Function with Hybrid Particle Swarm with Constraints

Zai Jun Wang; Bao Fu  Fang; Wei Liu

doi:10.4028/www.scientific.net/AMM.380-384.1510

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 380-384Multi-Agent Collaborative Research Based on an...

Multi-Agent Collaborative Research Based on an Optimization Method about Multiple Evaluation Function with Hybrid Particle Swarm with Constraints

Abstract:

This paper presents an optimization method about multiple evaluation function with hybrid particle swarm with constraints on the base of an optimization algorithm of hybrid particle swarm, which is used to solve the problem of multi-agent collaboration in the rescue simulation system. The optimization process uses a variety of evaluation function and also calculates the constraint relationship among the evaluation functions on the particle iterative process in order to obtain multi-objective optimization results that meet multiple conditions. The method is suitable for the collaborative problem among a variety of heterogeneous agents, which presents the collaboration among heterogeneous agents through constraints. The method proves to be effective in the practical application of the rescue simulation system.

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Periodical:

Applied Mechanics and Materials (Volumes 380-384)

Pages:

1510-1514

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.380-384.1510

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Online since:

August 2013

Authors:

Zai Jun Wang, Bao Fu Fang, Wei Liu

Keywords:

Hybrid Particle Swarm Optimization, Multi-Agent System (MAS), Rescue Robot

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