基于二阶段随机规划的城市医疗废弃物回收网络设计

doi:10.16381/j.cnki.issn1003-207x.2018.0943

中国管理科学 ›› 2021, Vol. 29 ›› Issue (5): 166-172.doi: 10.16381/j.cnki.issn1003-207x.2018.0943

基于二阶段随机规划的城市医疗废弃物回收网络设计

蒲松¹, 夏嫦²

1. 成都工业学院经济与管理学院, 四川成都 611730;
2. 成都文理学院经济与管理学院, 四川成都 610401

收稿日期:2018-07-04 修回日期:2019-05-07 出版日期:2021-05-20 发布日期:2021-05-26
通讯作者: 蒲松(1981-),男(汉族),四川绵阳人,成都工业学院经济与管理学院,副教授,博士(后),研究方向:物流系统优化,E-mail:028pusong@163.com. E-mail:028pusong@163.com.
基金资助:
国家自然科学基金重点资助项目（71432003）；教育厅哲学社会科学重点研究基地项目（XHJJ-1780，SCUAV20-A001）；成都工业学院人才引进项目（2017RC021）

A Two-stage Stochastic Programming Approach for Urban Medical Waste Recycling Network Design

PU Song¹, XIA Chang²

1. School of Economics and Management, Chengdu Technological University, Chengdu 610031, China;
2. School of Economics and Management, Chengdu College of Arts and Sciences, Chengdu 610401, China

Received:2018-07-04 Revised:2019-05-07 Online:2021-05-20 Published:2021-05-26

摘要/Abstract

摘要： 城市医疗废弃物日益增加，且回收需求量受诸多因素的影响，难以准确预测，假定回收需求为确定值的医疗废弃物网络优化设计不能与实际需求相匹配。本文考虑了离散随机参数环境下，医疗回收网络设计中选址规划、分配计划及运输规划的协同优化问题，建立了以选址成本、运输成本最小为目标，设施与车辆能力限制为约束的二阶段随机规划模型。根据模型特点，设计了基于Benders decomposition的求解算法，同时，设计了一系列加速技术用于提高算法的求解效率。最后，以国内某城市医疗回收网络为背景设计算例，检验本文模型和求解策略的可行性和有效性。结果表明：相比确定性规划，随机规划的解能够节约总成本，结合一系列加速技术的Benders decomposition方法比CPLEX与纯的Benders decomposition更有优势。

关键词: 城市医疗废弃物, 网络设计, 随机规划, Benders decomposition, 加速技术

Abstract: The urban medical waste demand increases greatly, which is also difficult to be determined accurately with the influence of many factors. Therefore, the model for urban medical waste recycling network design model with deterministic recycling demand might not match the actual demand. The problem that the location,assignment as well as transportation are optimized collaboratively is considered, and a two-stage stochastic programming model is built with minimizing the location cost and transportation cost as well as considering the facility and vehicle capacity constraints. And a benders decomposition algorithm is developed according to the model structure. In addition, a series of acceleration techniques are designed to improve the efficiency of this algorithm. Finally, the feasibility and effectiveness of the proposed model and solution strategy are verified through case studies which based on the certain city in China. The results show that the solution of stochastic programming can save more cost than the deterministic programming, and the benders decomposition method combined with a series of accelerating techniques has more advantages than the CPLEX and pure benders decomposition without any accelerating technique.

Key words: urban medical waste, network design, stochastic programming, benders decomposition, accelerating technique

中图分类号:

F252

蒲松, 夏嫦. 基于二阶段随机规划的城市医疗废弃物回收网络设计[J]. 中国管理科学, 2021, 29(5): 166-172.

PU Song, XIA Chang. A Two-stage Stochastic Programming Approach for Urban Medical Waste Recycling Network Design[J]. Chinese Journal of Management Science, 2021, 29(5): 166-172.

参考文献

[1] 中华人民共和国国务院.医疗废物管理条例[Z].2003.
[2] 石丽红. 城市医疗废弃物回收处理模式及其网络研究[D].大连:大连海事大学,2011.
[3] Da Silva C E, Hoppe A E, Ravanello M M, et al. Medical wastes management in the south of Brazil[J]. Waste Management, 2005, 25(6):600-605.
[4] 石丽红, 范厚明, 翟志伟,等. 城市医疗废弃物回收处理流程及车行路径优化[J]. 大连海事大学学报, 2010, 36(3):50-53.
[5] 谢斌福. 城市医疗废弃物回收处理模型应用及其回收网络优化研究[D].南京:南京大学, 2013.
[6] 王桂琳. 城市医疗废弃物回收网络选址-路径优化研究[D].大连:大连海事大学, 2011.
[7] Alumur S, Kara B Y. A new model for the hazardous waste location-routing problem[J]. Computers & Operations Research, 2007, 34(5):1406-1423.
[8] Samanlioglu F. A multi-objective mathematical model for the industrial hazardous waste location-routing problem[J]. European Journal of Operational Research, 2013, 226(2):332-340.
[9] Baldacci R, Mingozzi A, Wolfler Calvo R. An exact method for the capacitated location-routing problem[J]. Operations Research, 2011, 59(5):1284-1296.
[10] 赵亚东. 不确定条件下考虑环境影响的医疗废弃物物流运作优化研究[D].沈阳:东北大学, 2013.
[11] Lee C, Lee K, Park K, et al. Technical note-branch-and-price-and-cut approach to the robust network design problem without flow bifurcations[J]. Operations Research,2012,60(3):604-610.
[12] 张群, 卫李蓉. 逆向物流网络设计研究进展[J]. 中国管理科学, 2016, 24(9):165-176.
[13] Salema M I G, Barbosa-Povoa A P, Novais A Q. An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty[J]. European Journal of Operational Research, 2007, 179(3):1063-1077.
[14] Lee D H, Dong M. Dynamic network design for reverse logistics operations under uncertainty[J]. Transportation Research Part E Logistics & Transportation Review, 2009,45(1):61-71
[15] Soleimani H, Govindan K. Reverse logistics network design and planning utilizing conditional value at risk[J]. European Journal of Operational Research, 2014,237(2):487-497.
[16] Üster H, Memişoǧlu G. Biomass logistics network design under price-based supply and yield uncertainty[J]. Transportation Science, 2017,52(2):474-492.
[17] Kim K, Mehrotra S. A two-stage stochastic integer programming approach to integrated staffing and scheduling with application to nurse management.[J]. Operations Research, 2015,63:1431-1451.
[18] Magnanti T L, Wong R T. Accelerating benders decomposition:Algorithmic enhancement and model selection criteria[J]. Operations Research, 1981, 29(3):464-484.
[19] Adulyasak Y, Cordeau J F, Jans R. Benders decomposition for production routing under demand uncertainty[J]. Operations Research, 2015, 63(4):851-867.
[20] 刁在筠. 运筹学[M].北京:高等教育出版社, 2001.
[21] Santoso T, Ahmed S, Goetschalckx M, et al. A stochastic programming approach for supply chain network design under uncertainty[J]. European Journal of Operational Research, 2005, 167(1):96-115.

基于二阶段随机规划的城市医疗废弃物回收网络设计

A Two-stage Stochastic Programming Approach for Urban Medical Waste Recycling Network Design

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