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- W4383567211 abstract "Single-objective bounded optimization problems are widely used in real-world applications. Various evolutionary algorithms have been proposed to solve these problems. The Simulated Annealing Algorithm is one of the most popular algorithms with the advantage of fast convergence. When the problems have numerous local optimums, SA may fall into the first few local optimums. In this paper, to avoid falling into the local optimums, a Group Simulated Annealing Algorithm is proposed with a group strategy that separated each solution in the group for the annealing strategy. To assess the performance of the proposed algorithm, empirical experiments have been conducted on the test problems ICSI-OC 2022 with the comparison of the Simulated Annealing Algorithm." @default.
- W4383567211 created "2023-07-08" @default.
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- W4383567211 date "2023-01-01" @default.
- W4383567211 modified "2023-09-25" @default.
- W4383567211 title "Group Simulated Annealing Algorithm for ICSI-OC 2022" @default.
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- W4383567211 doi "https://doi.org/10.1007/978-3-031-36625-3_42" @default.
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