The vehicle routing programming of municipal solid waste collection under cognitive uncertainty

被引:1
作者
Wang, Zhen [1 ]
Huo, Jiazhen [2 ,3 ,4 ]
Lam, Jasmine Siu Lee [5 ]
机构
[1] Shandong Univ Finance & Econ, Int Sch Low Carbon Studies, Jinan, Shandong, Peoples R China
[2] Tongji Univ, Sch Econ & Management, Shanghai, Peoples R China
[3] Bosch Tongji Univ, Chair Global Supply Chain Management, Shanghai, Peoples R China
[4] Shanghai Zhongqiao Vocat & Tech Univ, Sch Econ & Management, Shanghai, Peoples R China
[5] Tech Univ Denmark, Dept Technol Management & Econ, Copenhagen, Denmark
基金
中国国家自然科学基金;
关键词
cognitive uncertainty; municipal solid waste collection; uncertainty modeling; uncertainty theory; vehicle routing; LOCAL SEARCH; EVOLUTIONARY ALGORITHM; SCHEDULING PROBLEMS; DEMAND UNCERTAINTY; GENETIC ALGORITHM; TIME WINDOWS; OPTIMIZATION; MANAGEMENT; METAHEURISTICS; SYSTEM;
D O I
10.1002/tjo3.12025
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
The rapid development of online shopping has led to an increase in express parcels, thus the proliferation of solid waste from parcel packaging. There are many other phenomena that have arisen with rapid economic development that also led to the surge in municipal solid waste. It is urgent to pay attention to municipal solid waste collection. Unexpected disruptive events lead to cognitive uncertainty and cause municipal waste collection to fail to function properly. This article studies how to properly carry out vehicle planning to achieve the shortest driving distance under cognitive uncertainty. The community's time window and the amount of garbage in each community are taken as uncertain variables. Based on the uncertainty theory, an uncertain vehicle routing problem (VRP) model and an uncertain VRP with the loading constraint model are constructed, and the solution algorithms of these two models are given. Several applications are carried out to evaluate the effectiveness of the proposed models and algorithms. This article proposes for the first time the models and algorithms to study the VRP under cognitive uncertainty. The findings draw important practical implications for adjusting municipal solid waste collection planning and logistics during disruptive events.
引用
收藏
页数:22
相关论文
共 95 条
[1]   A multi-objective closed-loop supply chain under uncertainty: An efficient Lagrangian relaxation reformulation using a neighborhood-based algorithm [J].
Ali, Syed Mithun ;
Fathollahi-Fard, Amir M. ;
Ahnaf, Rashik ;
Wong, Kuan Yew .
JOURNAL OF CLEANER PRODUCTION, 2023, 423
[2]   Routing and resource allocation in non-profit settings with equity and efficiency measures under demand uncertainty [J].
Alkaabneh, Faisal ;
Shehadeh, Karmel S. ;
Diabat, Ali .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2023, 149
[3]   Selective vehicle routing problems under uncertainty without recourse [J].
Allahviranloo, Mandieh ;
Chow, Joseph Y. J. ;
Recker, Will W. .
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2014, 62 :68-88
[4]   The secure time-dependent vehicle routing problem with uncertain demands [J].
Allahyari, Somayeh ;
Yaghoubi, Saeed ;
Van Woensel, Tom .
COMPUTERS & OPERATIONS RESEARCH, 2021, 131
[5]   A robust multi-objective routing problem for heavy-duty electric trucks with uncertain energy consumption [J].
Amiri, Afsane ;
Zolfagharinia, Hossein ;
Amin, Saman Hassanzadeh .
COMPUTERS & INDUSTRIAL ENGINEERING, 2023, 178
[6]  
[Anonymous], 2015, Uncertainty Theory
[7]   Municipal Solid Waste Collection and Management Problems: A Literature Review [J].
Belien, Jeroen ;
De Boeck, Liesje ;
Van Ackere, Jonas .
TRANSPORTATION SCIENCE, 2014, 48 (01) :78-102
[8]  
Beltrami E.J., 1974, NETWORKS, V4, P65, DOI DOI 10.1002/NET.3230040106
[9]   Metaheuristics for the waste collection vehicle routing problem with time windows, driver rest period and multiple disposal facilities [J].
Benjamin, A. M. ;
Beasley, J. E. .
COMPUTERS & OPERATIONS RESEARCH, 2010, 37 (12) :2270-2280
[10]   A two-stage hybrid local search for the vehicle routing problem with time windows [J].
Bent, R ;
Van Hentenryck, P .
TRANSPORTATION SCIENCE, 2004, 38 (04) :515-530