Research on the Optimization Approach for Cargo Oil Tank Design Based on the Improved Particle Swarm Optimization Algorithm

doi:10.1007/s12204-015-1663-2

上海交通大学学报（英文版） ›› 2015, Vol. 20 ›› Issue (5): 565-570.doi: 10.1007/s12204-015-1663-2

Research on the Optimization Approach for Cargo Oil Tank Design Based on the Improved Particle Swarm Optimization Algorithm

JIANG Wen-ying (姜文英), LIN Yan* (林焰), CHEN Ming (陈明), YU Yan-yun (于雁云)

(Ship CAD Engineering Centre, Dalian University of Technology, Dalian 116023, Liaoning, China)

发布日期:2015-10-29
通讯作者: LIN Yan (林焰) E-mail:inyanly@dlut.edu.cn

Research on the Optimization Approach for Cargo Oil Tank Design Based on the Improved Particle Swarm Optimization Algorithm

JIANG Wen-ying (姜文英), LIN Yan* (林焰), CHEN Ming (陈明), YU Yan-yun (于雁云)

(Ship CAD Engineering Centre, Dalian University of Technology, Dalian 116023, Liaoning, China)

Published:2015-10-29
Contact: LIN Yan (林焰) E-mail:inyanly@dlut.edu.cn

摘要/Abstract

摘要： Based on the improved particle swarm optimization (PSO) algorithm, an optimization approach for the cargo oil tank design (COTD) is presented in this paper. The purpose is to design an optimal overall dimension of the cargo oil tank (COT) under various kinds of constraints in the preliminary design stage. A non-linear programming model is built to simulate the optimization design, in which the requirements and rules for COTD are used as the constraints. Considering the distance between the inner shell and hull, a fuzzy constraint is used to express the feasibility degree of the double-hull configuration. In terms of the characteristic of COTD, the PSO algorithm is improved to solve this problem. A bivariate extremum strategy is presented to deal with the fuzzy constraint, by which the maximum and minimum cargo capacities are obtained simultaneously. Finally, the simulation demonstrates the feasibility and effectiveness of the proposed approach.

关键词: cargo oil tank optimization design, nonlinear programming, improved particle swarm optimization (PSO) algorithm, fuzzy constraint, construction feasibility degree

Abstract: Based on the improved particle swarm optimization (PSO) algorithm, an optimization approach for the cargo oil tank design (COTD) is presented in this paper. The purpose is to design an optimal overall dimension of the cargo oil tank (COT) under various kinds of constraints in the preliminary design stage. A non-linear programming model is built to simulate the optimization design, in which the requirements and rules for COTD are used as the constraints. Considering the distance between the inner shell and hull, a fuzzy constraint is used to express the feasibility degree of the double-hull configuration. In terms of the characteristic of COTD, the PSO algorithm is improved to solve this problem. A bivariate extremum strategy is presented to deal with the fuzzy constraint, by which the maximum and minimum cargo capacities are obtained simultaneously. Finally, the simulation demonstrates the feasibility and effectiveness of the proposed approach.

Key words: cargo oil tank optimization design, nonlinear programming, improved particle swarm optimization (PSO) algorithm, fuzzy constraint, construction feasibility degree

中图分类号:

U 662.2

JIANG Wen-ying (姜文英), LIN Yan* (林焰), CHEN Ming (陈明), YU Yan-yun (于雁云). Research on the Optimization Approach for Cargo Oil Tank Design Based on the Improved Particle Swarm Optimization Algorithm[J]. 上海交通大学学报（英文版）, 2015, 20(5): 565-570.

JIANG Wen-ying (姜文英), LIN Yan* (林焰), CHEN Ming (陈明), YU Yan-yun (于雁云). Research on the Optimization Approach for Cargo Oil Tank Design Based on the Improved Particle Swarm Optimization Algorithm[J]. Journal of shanghai Jiaotong University (Science), 2015, 20(5): 565-570.

参考文献 8

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Research on the Optimization Approach for Cargo Oil Tank Design Based on the Improved Particle Swarm Optimization Algorithm

Research on the Optimization Approach for Cargo Oil Tank Design Based on the Improved Particle Swarm Optimization Algorithm

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