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

被引:66
|
作者
Li, Jun-qing [1 ,2 ]
Han, Yun-qi [1 ]
Duan, Pei-yong [1 ]
Han, Yu-yan [2 ]
Niu, Ben [1 ]
Li, Cheng-dong [3 ]
Zheng, Zhi-xin [2 ]
Liu, Yi-ping [4 ]
机构
[1] Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250014, Peoples R China
[2] Liaocheng Univ, Sch Comp, Liaocheng 252059, Shandong, Peoples R China
[3] Shandong Jianzhu Univ, Sch Informat & Elect Engn, Jinan 252101, Peoples R China
[4] Osaka Prefecture Univ, Dept Comp Sci & Intelligent Syst, Sakai, Osaka 5998531, Japan
基金
美国国家科学基金会;
关键词
Vehicle routing problem; Time window; Synchronized visit; Artificial bee colony; Energy consumptions; LARGE NEIGHBORHOOD SEARCH; BEE COLONY ALGORITHM; LOCAL SEARCH; OPTIMIZATION;
D O I
10.1016/j.jclepro.2019.119464
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页数:14
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