A hybrid cuckoo search and genetic algorithm for reliability–redundancy allocation problems

• Published in: Computers & industrial engineering Vol. 66; no. 4; pp. 1115 - 1124
• Main Authors: Kanagaraj, G., Ponnambalam, S.G., Jawahar, N.
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.12.2013; Pergamon Press Inc
• Subjects: Cuckoo search; Genetic algorithm; Genetic algorithms; Heuristic; Hybrid evolutionary algorithm; Mathematical problems; Optimization algorithms; Reliability and redundancy allocation; Resource allocation; Studies; Cuckoo search; Reliability and redundancy allocation; Hybrid evolutionary algorithm; Genetic algorithm
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2013.08.003

•Research is on reliability–redundancy allocation problem.•Hybrid cuckoo and genetic algorithm proposed.•Benchmark problems used to evaluate the proposed algorithm.•Proposed hybrid performs better. Solving reliability and redundancy allocation problems via meta-heuristic algorithms has attracted increasing attention in recent years. In this study, a recently developed meta-heuristic optimization algorithm cuckoo search (CS) is hybridized with well-known genetic algorithm (GA) called CS–GA is proposed to solve the reliability and redundancy allocation problem. By embedding the genetic operators in standard CS, the balance between the exploration and exploitation ability further improved and more search space are observed during the algorithms’ performance. The computational results carried out on four classical reliability–redundancy allocation problems taken from the literature confirm the validity of the proposed algorithm. Experimental results are presented and compared with the best known solutions. The comparison results with other evolutionary optimization methods demonstrate that the proposed CS–GA algorithm proves to be extremely effective and efficient at locating optimal solutions.