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4PL routing problem using hybrid beetle swarm optimization
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DOI：10.1007/s00500-023-08378-4.png)
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摘要
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From the view of comprehensive consideration, this considers the uncertainty of transportation time and cost due to seasonality and human factors, and a multi-objective chance constrained programming model with minimum transportation time and cost was established. Due to the complexity of the problem, traditional algorithms are not enough, and more efficient optimization algorithms are still needed. According to the characteristics of the problem, the beetle antennae search (BAS) with one beetle is changed into multiple beetles, and Dijkstra algorithm is embedded, a hybrid beetle swarm optimization algorithm (HBSO) is designed to solve the problem, and the case analysis and algorithm analysis are made for three different examples; the datasets are referenced in literature (Lu et al. in Computer Integrated Manufacturing Systems 5:10-14, 2020). Under the three examples, the influence of the customer on the time and cost is different. The confidence level and weight of cost and time have great influence on the decision results. 4PL provider will not affect the choice of transportation route, but will change the choice of 3PL supplier and transportation mode. HBSO is an effective method to solve this problem. It is proved on efficiency, effectiveness and reliability in experiments by comparing with GA, PSO and BAS.
Keyword:
Fourth party logistics
Routing problem
Chance constrained programming
Beetle swarm algorithm
Dijkstra algorithm
期刊
IF:
2.5
论文数:
1.0W
被引数:
2.1W
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