A Novel Modified Tree‐Seed Algorithm for High‐Dimensional Optimization Problems. Issue 2 (1st March 2020)

• Record Type: Journal Article
• Authors: Zhao, Shijie; Gao, Leifu; Tu, Jun; Yu, Dongmei
• Is Part Of: Chinese journal of electronics. Volume 29:Issue 2(2020)
• Page Start: 337
• Page End: 343
• Publication Date: 2020-03-01
• Subjects: Tree‐seed algorithm -- Seed domain shrinkage -- Local reinforcement -- High‐dimension optimization; convergence -- gradient methods -- iterative methods -- optimisation -- probability -- trees (mathematics); probabilities -- adjacent‐generation best trees -- local reinforcement strategy -- seed domain shrinkable coefficient -- MTSA -- novel modified tree‐seed algorithm -- SDSC -- convergence efficiency -- local optima avoidance -- local exploitation process -- LRS strategy -- global exploration -- offspring seeds -- gradient information -- control parameter -- high‐dimensional continuous optimization problems -- high‐dimensional optimization problems; Electronics -- Periodicals; Electronics -- China -- Periodicals; Electronics; China; Periodicals; 621.38105
• DOI: 10.1049/cje.2020.01.012
• Languages: English
• ISSNs: 1022-4653

Abstract

Abstract : To efficiently handle high‐dimensional continuous optimization problems, a Modified tree‐seed algorithm(MTSA) is proposed by coupling a newly introduced control parameter named as Seed domain shrinkable coefficient(SDSC) and Local reinforcement strategy(LRS) based on gradient information of adjacentgeneration best trees. SDSC is dynamically decreased with iterations to adjust the produced domain of offspring seeds, for achieving the tradeoff between the global exploration and local exploitation. LRS strategy is to execute local exploitation process by employing gradient information of two best trees, for enhancing convergence efficiency and local optima avoidance with probabilities. The compared experimental results show the different effects of differenttype SDSC on MTSA, the faster convergence efficiency and the stronger robustness of the proposed MTSA.