The cooperation search algorithm (CSA) randomly generates a set of candidate solutions in the problem space, and then three operators are repeatedly executed until the stopping criterion is met: the team communication operator is used to improve the global exploration and determine the promising search area; the reflective learning operator is used to achieve a comprise between exploration and exploitation; the internal competition operator is used to choose solutions with better performances for the next cycle.
인용 양식
Feng, Zhong-kai, et al. “Cooperation Search Algorithm: A Novel Metaheuristic Evolutionary Intelligence Algorithm for Numerical Optimization and Engineering Optimization Problems.” Applied Soft Computing, vol. 98, Elsevier BV, Jan. 2021, p. 106734, doi:10.1016/j.asoc.2020.106734.
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