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A co-evolutionary improved multi-ant colony optimization for ship multiple and branch pipe route design

机译:共同进化改进的多蚁群优化算法,用于船舶多管支管设计

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This paper presents a co-evolutionary improved multi-ant colony optimization (CIMACO) algorithm for ship multi and branch pipe route design. The purpose of CIMACO algorithm is to design appropriate pipe routes to connect the starting points and ending points in the layout space under various kinds of constraints. The ant colony optimization (ACO) algorithm is improved according to the characteristics of ship pipe routing which is used to solve the single pipe routing problem. Based on the improved ACO algorithm, the multi ant colony optimization (MACO) algorithm with co-evolution mechanism is used to solve the multi and branch pipe routing problem. In this paper, the pheromone direction information and pheromone extension process are developed in the proposed algorithm to improve the calculation performance. Compared with conventional method, CIMACO algorithm is better at avoiding the problem of local optimum and accelerating the convergence rate. Finally, the simulation results demonstrate the feasibility and efficiency of the proposed algorithm. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文提出了一种共同进化的改进多蚁群算法(CIMACO),用于船舶多分支支路设计。 CIMACO算法的目的是设计适当的管道路线,以在各种约束条件下连接布局空间中的起点和终点。针对舰船管道调度的特点,对蚁群优化算法进行了改进,解决了单管道调度问题。在改进的ACO算法的基础上,采用协同进化机制的多蚁群算法(MACO)来解决多分支和分支管道的路由问题。本文提出了信息素方向信息和信息素扩展过程,以提高计算性能。与传统方法相比,CIMACO算法在避免局部最优和加快收敛速度​​方面具有更好的优势。最后,仿真结果证明了该算法的可行性和有效性。 (C)2015 Elsevier Ltd.保留所有权利。

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