Hybridizing sine cosine algorithm with multi-orthogonal search strategy for engineering design problems

Abstract

AbstractThis 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.Highlights MOSCA is presented to solve design and manufacturing optimization problems efficiently. MOSCA is based on two phases namely, sine cosine algorithm (SCA) and multi-orthogonal search strategy (MOSS). The integrated MOSCA enhances exploration tendency and exploitation capability. The MOSCA can be more robust, statistically sound, and quickly convergent. New approach produced successful results compared to the literature studies.