Güvenç, UğurDuman, SerhatHınıslıoğlu, Yunus2020-04-302020-04-302017978-1-5090-5795-5https://hdl.handle.net/20.500.12684/3033IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA) -- JUL 03-05, 2017 -- Gdynia, POLANDGUVENC, Ugur/0000-0002-5193-7990; Duman, Serhat/0000-0002-1091-125XWOS: 000450992400017Moth Swarm Algorithm (MSA) is one of the newest developed nature-inspired heuristics for optimization problem. Nevertheless MSA has a drawback which is slow convergence. Chaos is incorporated into MSA to eliminate this drawback. In this paper, ten chaotic maps have been embedded into MSA to find the best numbers of prospectors for increase the exploitation of the best promising solutions. The proposed method is applied to solve the well-known seven benchmark test functions. Simulation results show that chaotic maps can improve the performance of the original MSA in terms of the convergence speed. At the same time, sinusoidal map is the best map for improving the performance of MSA significantly.eninfo:eu-repo/semantics/closedAccesschaotic mapsoptimizationmoth swarm algorithmConference Object9095N/A