Location-routing Problem of Emergency Logistics for Engineering Construction Projects Under Complex Environments

被引：0
|
作者：
Zhang J. [1 ,2 ,3 ]
Zhu H.-X. [1 ]
Shen H. [1 ]
Li G.-Q. [2 ,3 ]
机构：
[1] School of Transportation and Logistics, Southwest Jiaotong University, Chengdu
[2] National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu
[3] National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2023年 / 23卷 / 03期
关键词：
emergency logistics; engineering construction projects; Gurobi; location routing problem; logistics engineering; road congestion;
D O I：
10.16097/j.cnki.1009-6744.2023.03.029
中图分类号：
学科分类号：
摘要：
Emergency material security is the key to post-disaster emergency relief in engineering and construction projects under complex environments. This paper addresses an emergency logistics center location-routing problem, taking into account demand uncertainty, congestion time uncertainty, maximum rescue time requirements, multi-type vehicles, and other factors. This paper adopts triangular fuzzy numbers to inscribe uncertain parameters and constructs a two-stage fuzzy nonlinear location-routing model based on scenarios. A single-objective deterministic model is obtained by integration, linearization and defuzzification, and the Gurobi solver is used to solve it. A super large railroad construction project in the mountainous region of the western plateau of Sichuan Province is taken as an example, and the validity and applicability of the model are verified through model comparison and sensitivity analysis. The results show that as the number of locations increases, storage costs increase by 5.9%, response times for the five scenarios are reduced by an average of 15.2% and the maximum response time is reduced by 7.8%. Compared with the Expected-value model, the model built in this paper is superior in terms of storage cost and emergency response time. The storage cost is linearly related to the demand level, while the maximum response time is affected by both the demand level and the congestion time. The model established in this paper can scientifically select the location of emergency facilities and develop emergency rescue paths to reduce the storage cost and response time of emergency rescue. It can provide decision support for dispatching emergency materials for engineering construction projects in complex and difficult areas. © 2023 Science Press. All rights reserved.
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页码：280 / 289
页数：9
相关论文
共 15 条
  • [1] ZENC M C, CU1 Z S, YU C H., Research on location-routing problem of relief system based on emergency logistics, Chinese Journal of Management Science, 18, 2, pp. 75-80, (2010)
  • [2] TAVANA M, ABTAH1 A-R, DI CAPRIO D, Et al., An integrated location-inventory-routing humanitarian supply chain network with pre-and post-disaster management considerations, J. Socio-Economic Planning Sciences, 64, pp. 21-37, (2018)
  • [3] LWANG D P, XL Z, YANG C., Study on location-routing problem of logistics distribution based on two-stage heuristic algorithm, Operations Research and Management Science, 26, 4, pp. 70-75, (2017)
  • [4] WU W T, WANC D L, MA C X., Model and algorithm for inventory routing problem of liquified natural gas, China Journal of Highway and Transport, 35, 11, (2022)
  • [5] CAUNHYE A M, ZHANG Y, LI M, Et al., A location-routing model for prepositioning and distributing emergency supplies, Transportation Research Part E: Logistics and Transportation Review, 90, pp. 161-176, (2016)
  • [6] ZHONG S, CHENG R, JIANG Y, Et al., Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand, Transportation Research Part E: Logistics and Transportation Review, 141, (2020)
  • [7] AHMADI M, SEIFI A, TOOTOONI B., A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district, Transportation Research Part E: Logistics and Transportation Review, 75, pp. 145-163, (2015)
  • [8] SABOUHI F, BOZORGI-AMIRI A, VAEZ P., Stochastic optimization for transportation planning in disaster relief under disruption and uncertainty, Kybernetes, 50, 9, pp. 2632-2650, (2020)
  • [9] CHEN G, ZHANG J, FU J Y., A multi-objective location-allocation model for emergency logistics in an uncertain information environment^], China Safety Science Journal, 26, 12, pp. 163-168, (2016)
  • [10] FAZAYELI S, EYDI A, KAMALABADI I N., Location-routing problem in multimodal transportation network with time windows and fuzzy demands: Presenting a two-part genetic algorithm, Computers & Industrial Engineering, 119, pp. 233-246, (2018)
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