Any potential damage may be severe once an accident occurs involving hazardous materials. It is therefore important to consider the risk factor concerning hazardous material supply chains, in order to make the best inventory routing decisions. This paper addresses the problem of hazardous material multi-period inventory routing with the assumption of a limited production capacity of a given manufacturer. The goal is to achieve the manufacturer’s production plan, the retailer’s supply schedule and the transportation routes within a fixed period. As the distribution of hazardous materials over a certain period is essentially a multiple travelling salesmen problem, the authors formulate a loading-dependent risk model for multiple-vehicle transportation and present an integer programming model to maximize the supply chain profit. An improved genetic algorithm considering two dimensions of chromosomes that cover the aforementioned period and supply quantity is devised to handle the integer programming model. Numerical experiments carried out demonstrate that using the proposed multi-period joint decision-making can significantly increase the overall profit of the supply chain as compared to the use of single period decision repeatedly, while effectively reducing its risk.
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This research was supported by the National Natural Science Foundation of China under Grant Nos. 71571010, 71722007, a Fundamental Research Funds for the Central Universities under Grant No. XK1802-5, a Ser Cymru II COFUND Research Fellowship, UK, and a Great Wall Scholar Training Program of Beijing Municipality under Grant No. CIT&TCD20180305.
This paper was recommended for publication by Editor WANG Shouyang.
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Hu, H., Li, J., Li, X. et al. Modeling and Solving a Multi-Period Inventory Fulfilling and Routing Problem for Hazardous Materials. J Syst Sci Complex 33, 760–782 (2020). https://doi.org/10.1007/s11424-019-8176-2
- Genetic algorithm
- integer programming model
- limited production capacity
- multi-period inventory routing problem