A new chaotic hybrid cognitive optimization algorithm. (December 2018)

• Record Type: Journal Article
• Authors: Zhou, Yuhong; Su, Ke; Shao, Limin
• Is Part Of: Cognitive systems research. Volume 52(2018)
• Page Start: 537
• Page End: 542
• Publication Date: 2018-12
• Subjects: Chaos -- Particle swarm optimization (PSO) -- Hybrid optimization algorithm; Cognition -- Periodicals; Cognitive engineering (System design) -- Periodicals; Artificial intelligence -- Periodicals; 153.05
• DOI: 10.1016/j.cogsys.2018.08.001
• Languages: English
• ISSNs: 1389-0417

Abstract

Abstract: To solve the optimization problems in port planning and operation management, particle swarm optimization, Cat mapping, and cloud model were combined. A Chaos Cloud Particle Swarm Optimization (CCPSO) algorithm was proposed. It was used in port planning management. Its application in port throughput forecasting and berthing and pontoon bridge allocation was explored and studied. By analyzing the mixed properties of Cat maps, the chaotic characteristics of the map were good. Thus, it was introduced into the hybrid optimization algorithm for chaotic perturbation of poor individuals in a particle swarm. The selection of the parameter combination of the Gauss-SVAR model was troublesome. The parameter combination of Guass-vSVR model was optimized by CCPSO algorithm, and the Guass-vSVR-CCPSO model was obtained. Using CCPSO algorithm, a discrete berth bridge allocation model was established. The results showed that the particle feasible integer processing module was developed. Therefore, a new method for multi-objective discrete berth shore-bridge allocation based on CCPSO algorithm is feasible.