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A hybridisation of Improved Harmony Search and Bacterial Foraging for multi-robot motion planning

Arindam Jati, Garima Singh, Pratyusha Rakshit, Amit Konar, Eunjin Kim, Atulya K. Nagar

Year
2012
Citations
11

Abstract

This paper provides a new approach to include the chemotactic behavior of Bacterial Foraging Algorithm (BFOA) in the existing Improved Harmony Search (IHS) algorithm. Extensive computer simulations with CEC-2005 benchmark functions reveal that the proposed algorithm outperforms the existing one with respect to accuracy in determining the optima. The proposed algorithm has successfully been implemented for multi-robot motion planning application. Performance has been studied using the proposed IHS-BFO algorithm and compared with existing IHS and Particle Swarm Optimization (PSO) algorithm.

Keywords

Harmony searchForagingComputer scienceParticle swarm optimizationBenchmark (surveying)Local optimumMathematical optimizationRobotMotion planningArtificial intelligence

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