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RISS 인기검색어
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- 저자 : Rizk-Allah, Rizk M. (검색결과 2 건)
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Rizk M. Rizk-Allah 한국CDE학회 2018 Journal of computational design and engineering Vol.5 No.2
This paper presents a new algorithm based on hybridizing the sine cosine algorithm (SCA) with a multi-orthogonal search strategy (MOSS), named multi-orthogonal sine cosine algorithm (MOSCA), for solving engineering design problems. The proposed MOSCA integrates the advantages of the SCA and MOSS to eliminate SCA’s disadvantages, like unbalanced exploitation and the trapping in local optima. The pro-posed MOSCA works in two stages, firstly, the SCA phase starts the search process to enhance exploration capability. Secondly, the MOSS phase starts its search from SCA found so far to boost the exploitation ten-dencies. In this regard, MOSS phase can assist SCA phase to search based on deeper exploration/exploita-tion patterns as an alternative. Therefore, the MOSCA can be more robust, statistically sound, and quickly convergent. The performance of the MOSCA algorithm is investigated by applying it on eighteen bench-mark problems and four engineering design problems. The experimental results indicate that MOSCA is a promising algorithm and outperforms the other algorithms in most cases.
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Rizk-Allah, Rizk M. Society for Computational Design and Engineering 2018 Journal of computational design and engineering Vol.5 No.2
This paper presents a new algorithm based on hybridizing the sine cosine algorithm (SCA) with a multi-orthogonal search strategy (MOSS), named multi-orthogonal sine cosine algorithm (MOSCA), for solving engineering design problems. The proposed MOSCA integrates the advantages of the SCA and MOSS to eliminate SCA's disadvantages, like unbalanced exploitation and the trapping in local optima. The proposed MOSCA works in two stages, firstly, the SCA phase starts the search process to enhance exploration capability. Secondly, the MOSS phase starts its search from SCA found so far to boost the exploitation tendencies. In this regard, MOSS phase can assist SCA phase to search based on deeper exploration/exploitation patterns as an alternative. Therefore, the MOSCA can be more robust, statistically sound, and quickly convergent. The performance of the MOSCA algorithm is investigated by applying it on eighteen benchmark problems and four engineering design problems. The experimental results indicate that MOSCA is a promising algorithm and outperforms the other algorithms in most cases.
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