Vehicle routing scheduling using an enhanced hybrid optimization approach

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• 作者：Behnam Vahdani (1) b.vahdani@gmail.com
  Reza Tavakkoli-Moghaddam (1)
  Mostafa Zandieh (2)
  Jafar Razmi (1)
• 关键词：Cross docking &#8211 ; Vehicle routing scheduling &#8211 ; Hybrid metaheuristic &#8211 ; Tabu search (TS) &#8211 ; Particle swarm optimization (PSO) &#8211 ; Variable neighborhood search (VNS) &#8211 ; Simulated annealing (SA) &#8211 ; Taguchi method
• 刊名：Journal of Intelligent Manufacturing
• 出版年：2012
• 出版时间：June 2012
• 年：2012
• 卷：23
• 期：3
• 页码：759-774
• 全文大小：706.3 KB
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• 作者单位：1. Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran2. Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, Iran
• 刊物类别：Business and Economics
• 刊物主题：Economics
  Production and Logistics
  Manufacturing, Machines and Tools
  Automation and Robotics
  
• 出版者：Springer Netherlands
• ISSN：1572-8145

文摘

Cross docking play an indispensable role in streamlining the efficiency and effectiveness of any supply chain operations. Owing to the need to reduce transportation lead time and increase coordination between other supply chain activities such as just-in-time, make-to-order, or merge-in-transit strategies, shortening the total transfer time at cross docking is increasing important. Thus, in this paper we propose a new hybrid metaheuristic for vehicle routing scheduling in cross-docking systems. This new hybrid algorithm incorporates the elements from Particle Swam Optimization, Simulated Annealing and Variable Neighborhood Search to enhance its search capabilities. On view of the fact that the performance of metaheuristic algorithms are considerably influenced by the proper tuning of their parameters, we take advantage of Taguchi’s robust design method to come up with the best parameters of the before-mentioned algorithms. In order to measure the performance of our proposed algorithm, we compared it with the Tabu Search algorithm presented by Lee et al. (Comput Ind Eng 51:247–256, 2006). The computational evaluations clearly support the high performance of our proposed algorithm against other algorithm in the literature.