Logistics 2009
DOI: 10.1061/40996(330)132
|View full text |Cite
|
Sign up to set email alerts
|

A Dynamic Multiple Objective Model of Location Problem of Emergency Logistics Distribution Centers

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Year Published

2016
2016
2024
2024

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(3 citation statements)
references
References 0 publications
0
3
0
Order By: Relevance
“…This paper refers to the research of Yu Dongmei [5] , and Zeng [6] , uses the robust optimization method of uncertainty set to study the location problem of emergency material storage, and establishes a multi-objective robust optimization model. In consideration of ε constraint method does not need to impose additional variables on the model or handle multiple objective functions proportionally [7] , only controls the generation of effective solution sets by appropriately adjusting each grid point within the scope of the objective function. Therefore, this paper uses ε constraint method transforms the multi-objective problem into a single objective optimization problem, and finally a universal immune algorithm is designed to solve it.…”
Section: Introductionmentioning
confidence: 99%
“…This paper refers to the research of Yu Dongmei [5] , and Zeng [6] , uses the robust optimization method of uncertainty set to study the location problem of emergency material storage, and establishes a multi-objective robust optimization model. In consideration of ε constraint method does not need to impose additional variables on the model or handle multiple objective functions proportionally [7] , only controls the generation of effective solution sets by appropriately adjusting each grid point within the scope of the objective function. Therefore, this paper uses ε constraint method transforms the multi-objective problem into a single objective optimization problem, and finally a universal immune algorithm is designed to solve it.…”
Section: Introductionmentioning
confidence: 99%
“…Murali et al [1] present locate-allocate heuristic for capacitated facility location to response large-scale emergencies under demand uncertainty. Shui et al [19] present a mixed integer programming model in order to determine the locations and amounts of the emergency logistics DCs. Yushimito et al [20] propose a heuristic algorithm based on Voronoi diagrams in order to solve the distribution center location problem.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The strategic decisions contain the location of DCs. The operational part [36] Unsatisfied Demand Minimization      Yushimito and Ukkusuri [28] Cost Minimization      Jia et al [3] Distance Minimization    Demand Chang et al [32] Distance Minimization      Demand Jia et al [4] Coverage Minimization     Günneç and Salman [35] Time and Risk Minimization      Demand Mete and Zabinsky [33] Cost and Time Minimization      Demand and time Balcik and Beamon [11] Coverage Maximization     Shui et al [19] Cost and Time Minimization     Mete and Zabinsky [34] Cost Minimization      Demand time and supply Rawls and Turnquist [5] Cost Minimization     Demand and link availability Salmeron and Apte [26] Unsatisfied Demand Minimization     Demand and time Huang et al [18] Coverage Maximization/Distance Minimization     Han et al [37] Distance Minimization     Verma and Gaukler [23] Distance Minimization     Distance Campell and Jones [28] Cost Minimization     Duran et al [21] Time Minimization     Demand/ Supply Rawls and Turnquist [22] Cost Minimization     Demand and link availability Bozorgi-Amiri et al [38] Cost Minimization      Procuring cost, demand and inventory Naji-Azimi et al [39] Distance Minimization   Döyen et al [24] Cost Minimization      Demand Yushimito et al [20] Cost Minimization and Coverage Maximization     Galindo and Batta [30] Cost Minimization     Demand Murali et al [1] Coverage Maximization    Demand Lin et al [40] Cost Minimization      Paul and Hariharan [41] Cost Minimization      Afshar and Haghani [42] Unsatisfied Demand Minimization     Rawls and Turnquist [43] Cost Minimization      Demand and link availability Hong et al [25] Cost Minimization     Demand and transportation capacity Lodree et al …”
Section: Literature Reviewmentioning
confidence: 99%