This article proposes a novel metaheuristic algorithm called Chimp Optimization Algorithm (ChOA) inspired by the individual intelligence and sexual motivation of chimps in their group hunting, which is different from the other social predators. ChOA is designed to further alleviate the two problems of slow convergence speed and trapping in local optima in solving high-dimensional problems. In this article, a mathematical model of diverse intelligence and sexual motivation is proposed. Four types of chimps entitled attacker, barrier, chaser, and driver are employed for simulating the diverse intelligence. Moreover, the four main steps of hunting, driving, blocking, and attacking, are implemented. Afterward, the algorithm is tested on 30 well-known benchmark functions, and the results are compared to four newly proposed meta-heuristic algorithms in term of convergence speed, the probability of getting stuck in local minimums, and the accuracy of obtained results. The results indicate that the ChOA outperforms the other benchmark optimization algorithms.
Khishe, M., and M. R. Mosavi. “Chimp Optimization Algorithm.” Expert Systems with Applications, vol. 149, Elsevier BV, July 2020, p. 113338, doi:10.1016/j.eswa.2020.113338.
M. Khishe, M. R. Mosavi (2020). Chimp Optimization Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/<...>), MATLAB Central File Exchange. Retrieved June 10, 2020.
How to import Excel values as a input to chimp optimization
Good job! Really incredible work.
May I ask Which part in MATLAB corresponds to the simulation of "Social incentive" that is described as follows: "To model this simultaneous behaviour, we assume that there is a probability of 50% to choose between either the normal updating position mechanism or the chaotic model to update the position of chimps during ptimization. "
near same GWO and EO
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