A branch-bound algorithm for the capacitated facilities location problem

The emergency service facilities location is one of the most important issues in the emergency management. This study focused on the location set covering problem (LSCP) for emergency service facilities under fuzzy environment. On the basis of defining the signed distance of trapezoidal fuzzy number, the ranking rules of trapezoidal fuzzy number are defined, the model of emergency service facilities location with fuzzy restraints is proposed, and the solution algorithm for the emergency service location based on the ordering rules of trapezoidal fuzzy number is given. Finally, a numerical simulation is used to illustrate the application of the method, which shows that the algorithm is feasible and advantageous.

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Solving the multiple competitive facilities location problem

European Journal of Operational Research ◽

10.1016/s0377-2217(01)00168-0 ◽

2002 ◽

Vol 142 (1) ◽

pp. 138-151 ◽

Cited By ~ 77

Author(s):

Tammy Drezner ◽

Zvi Drezner ◽

Said Salhi

Keyword(s):

Location Problem ◽

Facilities Location

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Hybrid Set Covering and Dynamic Modular Covering Location Problem: Application to an Emergency Humanitarian Logistics Problem

Applied Sciences ◽

10.3390/app10207110 ◽

2020 ◽

Vol 10 (20) ◽

pp. 7110 ◽

Cited By ~ 1

Author(s):

Roghayyeh Alizadeh ◽

Tatsushi Nishi

Keyword(s):

Location Problem ◽

Set Covering ◽

Strategic Decisions ◽

Maximal Covering ◽

Planning Decisions ◽

Tactical Decisions ◽

Covering Model ◽

Validation Tests ◽

Capacitated Facilities

This paper presents an extension of the covering location problem as a hybrid covering model that utilizes the set covering and maximal covering location problems. The developed model is a multi-period model that considers strategic and tactical planning decisions. Hybrid covering location problem (HCLP) determines the location of the capacitated facilities by using dynamic set covering location problem as strategic decisions and assigns the constructive units of facilities and allocates the demand points by using dynamic modular capacitated maximal covering location problem as tactical decisions. One of the applications of the proposed model is locating first aid centers in humanitarian logistic services that have been addressed by studying a threat case study in Japan. In addition to validating the developed model, it has been compared to other possible combined problems, and several randomly generated examples have been solved. The results of the case study and model validation tests approve that the main hybrid developed model (HCLP) is capable of providing better coverage percentage compared to conventional covering models and other hybrid variants.

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An integrated MILP-MCDM decision framework for uncertain multi-criteria facilities location problem of glass industries

International Journal of Management and Decision Making ◽

10.1504/ijmdm.2020.10023761 ◽

2020 ◽

Vol 19 (1) ◽

pp. 1

Author(s):

Sadegh Niroomand ◽

Nahid Kohansal ◽

Arash Bazyar ◽

Fereshteh Daneshdoost

Keyword(s):

Location Problem ◽

Decision Framework ◽

Facilities Location

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Congestion Service Facilities Location Problem with Promise of Response Time

Mathematical Problems in Engineering ◽

10.1155/2013/716534 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Dandan Hu ◽

Zhi-Wei Liu ◽

Wenshan Hu

Keyword(s):

Response Time ◽

Location Problem ◽

Service Providers ◽

Programming Model ◽

Mixed Integer ◽

Specific Response ◽

Location Decision ◽

Decision Variables ◽

Facilities Location ◽

Nonlinear Programming Model

In many services, promise of specific response time is advertised as a commitment by the service providers for the customer satisfaction. Congestion on service facilities could delay the delivery of the services and hurts the overall satisfaction. In this paper, congestion service facilities location problem with promise of response time is studied, and a mixed integer nonlinear programming model is presented with budget constrained. The facilities are modeled as M/M/c queues. The decision variables of the model are the locations of the service facilities and the number of servers at each facility. The objective function is to maximize the demands served within specific response time promised by the service provider. To solve this problem, we propose an algorithm that combines greedy and genetic algorithms. In order to verify the proposed algorithm, a lot of computational experiments are tested. And the results demonstrate that response time has a significant impact on location decision.

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Research on the Location Model of Emergency Rescue Facilities in the City Disaster Prevention

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.744-746.1745 ◽

2015 ◽

Vol 744-746 ◽

pp. 1745-1748 ◽

Cited By ~ 1

Author(s):

Qing Zhen Sun ◽

Yan Jia ◽

Xiao Ying Hou ◽

Peng Li

Keyword(s):

Decision Model ◽

Location Problem ◽

Location Decision ◽

Disaster Prevention ◽

Basic Principles ◽

Multi Objective ◽

Emergency Rescue ◽

Decision Method ◽

Facilities Location ◽

The City

In order to solve the location problem of the city disaster emergency rescue facilities, it applied the multi-objective decision method to resolve the problem. Firstly it described the types of emergency facilities in the city and proposed the basic principles of the location decision. Then it analyzed the four factors of the location decision, and it established the multi-objective decision model of the emergency rescue facilities location, which based on the integration of traditional location models. And then it used the linear weighted sum law to solve the model, and can readjust the weights of the goals to reach the satisfying plan. Finally, it applied the model to solve the emergency shelter location problem of the new area in the Zhengzhou. The result shows the feasibility and the effectiveness of the model which used the multi-objective decision method to solve the location problem of the city disaster emergency rescue facilities.

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