The Multi-Commodity Facilities Location Problem

1981 ◽  
Vol 32 (9) ◽  
pp. 803 ◽  
Author(s):  
J. Karkazis ◽  
T. B. Boffey
Keyword(s):  
Location Problem ◽  
Facilities Location

scholarly journals Modeling and Simulation of Emergency Service Facilities Location Problem Under Fuzzy Environment

2014 ◽  
Vol 8 (1) ◽  
pp. 48-52 ◽  
Author(s):  
Zixue Guo ◽  
Meiran Qi
Keyword(s):  
Fuzzy Number ◽  
Emergency Service ◽  
Location Problem ◽  
Set Covering ◽  
Covering Problem ◽  
Trapezoidal Fuzzy Number ◽  
Signed Distance ◽  
Fuzzy Environment ◽  
Facilities Location ◽  
Service Location

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.

Solving the multiple competitive facilities location problem

2002 ◽  
Vol 142 (1) ◽  
pp. 138-151 ◽  
Author(s):  
Tammy Drezner ◽  
Zvi Drezner ◽  
Said Salhi
Keyword(s):  
Location Problem ◽  
Facilities Location

scholarly journals Congestion Service Facilities Location Problem with Promise of Response Time

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
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.

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

2015 ◽  
Vol 744-746 ◽  
pp. 1745-1748 ◽  
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.

The Multi-Commodity Facilities Location Problem

1981 ◽  
Vol 32 (9) ◽  
pp. 803-814 ◽  
Author(s):  
J. Karkazis ◽  
T. B. Boffey
Keyword(s):  
Location Problem ◽  
Facilities Location

scholarly journals Development of set covering model for determining the open /closed facilities location and resizing capacity of fasilities

2020 ◽  
Vol 909 (1) ◽  
pp. 012082 ◽  
Author(s):  
Utaminingsih Linarti ◽  
Cahaya Annisa’ Fatonah ◽  
Annie Purwani
Keyword(s):  
Facility Location ◽  
Location Problem ◽  
Facility Location Problem ◽  
Set Covering ◽  
Second Stage ◽  
Basic Model ◽  
Facilities Location ◽  
Covering Model ◽  
Two Stages ◽  
The Cost

Abstract Set Covering model determines the location of facilities that can be used that minimize the cost of assigning facilities to the point of request with the limitation that each facility was used for a number points of request. If there is an imbalance between the volume of demand points and the capacity of the facilities, it is necessary to open/closed facilities. In fact, facility location problem can extended for the decision not only open/closed but rezising area the existing facilities that can be adjusted considering the avaibility area of facilities location and demand points. This case has not been accommodated on the basic model of set covering. Not all the existing facilities can be resized. Rezising the area of facility location was assumed discrete. The aims of this study was optimized the alghorithm of set covering model. The solution this study was devided into two stages. The first stage was screening facilities that can be resized with survey location. The second stage was set covering model which the facilities will be close/opened and resize the existing facilities.

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