A human-computer cooperation improved ant colony optimization for ship pipe route design. (15th February 2018)

• Record Type: Journal Article
• Authors: Wang, Yun-long; Yu, Yan-yun; Li, Kai; Zhao, Xue-guo; Guan, Guan
• Is Part Of: Ocean engineering. Volume 150(2018)
• Page Start: 12
• Page End: 20
• Publication Date: 2018-02-15
• Subjects: Ship pipe route design -- Optimization algorithm -- Human-computer cooperation -- Artificial solution -- Algorithm solution -- Ant colony algorithm; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2017.12.024
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: 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, it's hard to find 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. Highlights: This paper presents a human-computer cooperation improved ant colony optimization (HCCIACO) algorithm for ship pipe route design (SPRD). 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 ant colony optimization algorithm.