个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职:船舶工程学院副院长
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:船舶工程学院
学科:船舶与海洋结构物设计制造
办公地点:船舶学院205(船池楼)
联系方式:Tel:13591143518
电子邮箱:yunlongw@dlut.edu.cn
A human-computer cooperation improved ant colony optimization for ship pipe route design
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论文类型:期刊论文
发表时间:2018-02-15
发表刊物:OCEAN ENGINEERING
收录刊物:SCIE、EI
卷号:150
页面范围:12-20
ISSN号:0029-8018
关键字:Ship pipe route design; Optimization algorithm; Human-computer cooperation; Artificial solution; Algorithm solution; Ant colony algorithm
摘要:This paper presents a human-computer cooperation improved ant colony optimization (HCCIACO) algorithm for ship pipe route design (SPRD). SPRD is a conbinatorial optimization problem with various performance constraints, its hard to fmd an effective solution only by computer. Based on the human-computer cooperation theory, the HCCIACO algorithm takes full advantage of designers' expertise and experience as well as computers' calculation ability. It conbines the artificial sulotion and algorithm solution in the genetic sense of the improved ant colony optimization (IACO) algorithm so that the optimization approach for SPRD in three-dimensional space can be obtained. The improved ant colony optimization simplifies the problem by reducing the complexity in calculation and engineering to some extent. Meanwhile, it guides the algorithm to search effectively for the stable solution which satisfies the engineering requirements. in this paper, the structure and updating method of artificial solution as well as the combination mode of artificial solution and algorithm solution have been researched. Compare with the conventional mathod, HCCIACO algorithm not only improves the convergence speed, but also improves the quality of the solution. Finally, the simulation results demonstrate the feasibility and efficiency of the proposed algorithm.