A novel membrane algorithm for capacitated vehicle routing problem

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• 作者：Yunyun Niu (1)
  Shuo Wang (2)
  Juanjuan He (2)
  Jianhua Xiao (3)
  
  1. School of Electronic Engineering and Computer Science ; Peking University ; Beijing ; 100871 ; China
  2. Key Laboratory of Image Processing and Intelligent Control ; Department of Control Science and Engineering ; Huazhong University of Science and Technology ; Wuhan ; 430074 ; China
  3. The Research Center of Logistics ; Nankai University ; Tianjin ; 300071 ; China
  
• 关键词：Membrane algorithm ; Ant colony optimization ; Max鈥搈in ant system ; Capacitated vehicle routing problem
• 刊名：Soft Computing - A Fusion of Foundations, Methodologies and Applications
• 出版年：2015
• 出版时间：February 2015
• 年：2015
• 卷：19
• 期：2
• 页码：471-482
• 全文大小：692 KB
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• 刊物类别：Engineering
• 刊物主题：Numerical and Computational Methods in Engineering
  Theory of Computation
  Computing Methodologies
  Mathematical Logic and Foundations
  Control Engineering
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1433-7479

文摘

This study is focused on solving the capacitated vehicle routing problem (CVRP) by applying a novel membrane algorithm based on ant colony optimization (MA_ACO). The effect of non-determinism on the performance of the membrane algorithm is also studied in this work. In this approximate approach model, a membrane system is considered to be a non-deterministic distributed parallel framework, and ant colony optimization (ACO) is used as a sub-algorithm of elementary membranes. With the purpose of maintaining balance between the convergence rate and the population diversity, MA_ACO supports sub-algorithms for elementary membranes based on two types of ACO. The elementary membranes send their best solutions to the skin membrane. In the next step, the best one in the skin membrane is sent back to every inner membrane with a fixed probability. All of the elementary membranes have thus a chance to receive the best result and make changes to the current search direction. Thirty benchmark problems of CVRP are utilized to confirm the effectiveness of the proposed membrane algorithm. Experimental results show that compared with other algorithms proposed in the previous literature, our algorithm is very competitive. The new best solutions for seven instances are also listed.