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Particle swarm optimization (PSO) and Sine Cosine algorithm (SCA) have beenwidely used optimization methods but these methods have some disadvantages suchas trapped local optimum point. In order to solve this problem and obtain moresuccessful results than others, a novel logistic dynamic weight based sinecosine search algorithm (LDW-SCSA) is presented in this paper. In the LDW-SCSAmethod, logistic map is used as dynamic weight generator. Logistic map is oneof the famous and widely used chaotic map in the literature. Search process ofSCA is modified in the LDW-SCSA. To evaluate performance of the LDW-SCSA, thewidely used numerical benchmark functions were utilized as test suite and otherswarm optimization methods were used to obtain the comparison results. Superiorperformances of the LDW-SCSA are proved success of this method.

LDW-SCSA: Logistic Dynamic Weight based Sine Cosine Search Algorithm for Numerical Functions Optimization