Multi-objective Optimization using Cricket Chirping Algorithm
Jonti Deuri1, S. Siva Sathya2
1Jonti Deuri, Department of Computer Science, Pondicherry University, Pondicherry (Tamil Nadu), India.
2S. Siva Sathya, Department of Computer Science, Pondicherry University, Pondicherry (Tamil Nadu), India.
Manuscript received on 04 June 2019 | Revised Manuscript received on 29 June 2019 | Manuscript Published on 04 July 2019 | PP: 393-401 | Volume-8 Issue-1S4 June 2019 | Retrieval Number: A10710681S419/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Utmost real world optimization problems are typically multi-objective with complex constraints. Now-a-days the heuristics and meta-heuristics approaches are becoming more powerful to solve these optimization problems considerably to direct approach. Cricket Chirping Algorithm (CCA) is a metaheuristics approach developed based on the chirping behavior of cricket for solving optimization problem. In this paper the cricket chirping algorithm for single objective optimization is extended for solving multi-objective optimization problems by adopting the aggressive behavior of cricket. The proposed Multi-objective Optimization using Cricket Chirping Algorithm(MOCCA) is first validated with a subset of benchmark test functions and compared with the other metaheuristics algorithm like MOPSO, NSGA-II and SPEA-II. The performance, efficiency and robustness of the proposed algorithm are experimented and statistically analyzed and it is proved the superiority of the MOCCA to other methods in terms of diversity and convergence of the solution. It can provide optimal or near optimal solutions for a wide range of problems.
Keywords: Multi-objective Optimization, Cricket Chirping Algorithm, Meta-heuristics, Optimization Problem.
Scope of the Article: Algorithm Engineering