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The Pickup and Delivery Problem with Time Windows and Incompatibility Constraints in Cold Chain Transportation

皮卡 水准点(测量) 数学优化 冷链 计算机科学 功能(生物学) 供应链 质量(理念) 总成本 运筹学 数学 工程类 经济 业务 大地测量学 机械工程 地理 营销 微观经济学 人工智能 哲学 进化生物学 图像(数学) 认识论 生物
作者
Faheng Deng,Hu Qin,Jiliu Li,Chun Cheng
出处
期刊:Transportation Science [Institute for Operations Research and the Management Sciences]
卷期号:57 (2): 444-462 被引量:19
标识
DOI:10.1287/trsc.2022.1167
摘要

This study investigates a new variant of the pickup and delivery problem with time windows (PDPTW) applied in cold chain transportation, which quantifies the effect of time on the quality of perishable products. Multiple commodities with incompatibility constraints are considered, where some types of products cannot be transported in a vehicle simultaneously because of their different properties and requirements for storage temperatures. The aim is to determine vehicles’ pickup and delivery routes as well as their departure times from the depot such that the travel cost and refrigeration cost of vehicles and the quality decay cost of products are minimized. We formulate this problem as a set partitioning model, which is solved exactly by a tailored branch-and-price (B&P) algorithm. To tackle the asymmetry issue arising from the pricing problem of the B&P framework, we develop a novel asymmetric bidirectional labeling algorithm. Benchmark instance sets based on real-world statistical data and classic PDPTW instance sets are first generated for this problem. Numerical results show that our B&P algorithm can solve most instances to optimality in an acceptable time frame. Moreover, our results demonstrate that integrating the refrigeration and quality decay costs into the objective function can significantly lower the total cost of cold chain transportation activities, compared with the widely adopted objective function minimizing only the travel cost. Funding: This work was supported by the National Key R&D Program of China [Grant 2018YFB1700600] and the National Natural Science Foundation of China [Grants 72101049, 71971090, 71821001]. Supplemental Material: The online supplement is available at https://doi.org/10.1287/trsc.2022.1167 .
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