4.7 Article

Meta-heuristic algorithm for solving vehicle routing problems with time windows and synchronized visit constraints in prefabricated systems

期刊

JOURNAL OF CLEANER PRODUCTION
卷 250, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.119464

关键词

Vehicle routing problem; Time window; Synchronized visit; Artificial bee colony; Energy consumptions

资金

  1. National Science Foundation of China [61773192, 61803192, 61773246]
  2. Shandong Province Higher Educational Science and Technology Program [J17KZ005]
  3. State Key Laboratory of Synthetical Automation for Process Industries [PAL-N201602]
  4. Special Fund for Local Science and Technology Development Lead by Central Authority [ZR2018ZB0419]
  5. Major Basic Research Projects in Shandong [ZR2018ZB0419]
  6. Grant of Key Laboratory of Intelligent Optimization and Control with Big Data

向作者/读者索取更多资源

Prefabricated construction has attracted research interest as it can significantly improve the energy, cost, and time efficiency of construction. However, dispatching the required prefabricated components to construction sites in a prefabricated system is challenging. To address this issue, we modeled the dispatching problem as a special type of vehicle routing problem with time windows (VRPTW) and solved it by using an improved artificial bee colony (IABC) algorithm. First, to efficiently solve the cross-synchronization problem that occurs in prefabricated systems, two problem-specific lemmas were derived. Then, a hybrid initialization strategy was developed to generate feasible and efficient solutions and a well-designed encoding repair strategy was utilized to make solutions feasible. Finally, a variable length local search strategy was embedded to enhance the exploitation ability. To verify the performance of the proposed IABC algorithm, 55 instances were generated and used for simulation tests. Three efficient algorithms, including the two-phase genetic algorithm (TPGA), improved tabu search algorithm (ITSA), and adaptive large neighborhood search (ALNS) heuristic, were selected for detailed comparisons. Our simulation results show that, considering the energy consumption metric, the proposed algorithm yields average deviations of about 0.099, 0.096, and 0.143 times the values obtained with the TPGA, ITSA, and ALNS heuristic, respectively. The simulation results confirmed that the proposed algorithm can solve the VRPTW in prefabricated systems with high efficiency. (C) 2019 Elsevier Ltd. All rights reserved.

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