Advances in Computational Design

  • 제1권1호
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  • Pages.87-103
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  • 2016
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  • 2383-8477(pISSN)
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  • 2466-0523(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

An efficient multi-objective cuckoo search algorithm for design optimization

  • Kaveh, A. (Centre of Excellence for Fundamental Studies in Structural Engineering, Iran University of Science and Technology) ;
  • Bakhshpoori, T. (Centre of Excellence for Fundamental Studies in Structural Engineering, Iran University of Science and Technology)
  • 투고 : 2015.08.12
  • 심사 : 2015.09.09
  • 발행 : 2016.01.25
⟨ 이전 논문 다음 논문 ⟩

초록

This paper adopts and investigates the non-dominated sorting approach for extending the single-objective Cuckoo Search (CS) into a multi-objective framework. The proposed approach uses an archive composed of primary and secondary population to select and keep the non-dominated solutions at each generation instead of pairwise analogy used in the original Multi-objective Cuckoo Search (MOCS). Our simulations show that such a low computational complexity approach can enrich CS to incorporate multi-objective needs instead of considering multiple eggs for cuckoos used in the original MOCS. The proposed MOCS is tested on a set of multi-objective optimization problems and two well-studied engineering design optimization problems. Compared to MOCS and some other available multi-objective algorithms such as NSGA-II, our approach is found to be competitive while benefiting simplicity. Moreover, the proposed approach is simpler and is capable of finding a wide spread of solutions with good coverage and convergence to true Pareto optimal fronts.

키워드

참고문헌

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피인용 문헌

  1. A comparative study of multi-objective evolutionary metaheuristics for lattice girder design optimization vol.77, pp.3, 2016, https://doi.org/10.12989/sem.2021.77.3.417