A robust and efficient algorithm for planar competitive location problems

2007 ◽  
Vol 167 (1) ◽  
pp. 87-105 ◽  
Author(s):  
J. L. Redondo ◽  
J. Fernández ◽  
I. García ◽  
P. M. Ortigosa
Keyword(s):  
Efficient Algorithm ◽  
Location Problems ◽  
Competitive Location

TWO BI-OBJECTIVE OPTIMIZATION MODELS FOR COMPETITIVE LOCATION PROBLEMS

2006 ◽  
Vol 05 (03) ◽  
pp. 531-543 ◽  
Author(s):  
FENGMEI YANG ◽  
GUOWEI HUA ◽  
HIROSHI INOUE ◽  
JIANMING SHI
Keyword(s):  
Integer Programming ◽  
Programming Problem ◽  
Efficient Solutions ◽  
Integer Program ◽  
Location Problems ◽  
Optimization Models ◽  
Competitive Location ◽  
Integer Programming Problem ◽  
Single Objective ◽  
Parametric Integer Programming

This paper deals with two bi-objective models arising from competitive location problems. The first model simultaneously intends to maximize market share and to minimize cost. The second one aims to maximize both profit and the profit margin. We study some of the related properties of the models, examine relations between the models and a single objective parametric integer programming problem, and then show how both bi-objective location problems can be solved through the use of a single objective parametric integer program. Based on this, we propose two methods of obtaining a set of efficient solutions to the problems of fundamental approach. Finally, a numerical example is presented to illustrate the solution techniques.

Two-Swarm PSO for Competitive Location Problems

2009 ◽  
pp. 115-126 ◽  
Author(s):  
Clara M. Campos Rodríguez ◽  
José A. Moreno Pérez ◽  
Hartmut Noltemeier ◽  
Dolores R. Santos Peñate
Keyword(s):  
Location Problems ◽  
Competitive Location

New heuristic algorithms for discrete competitive location problems with binary and partially binary customer behavior

2017 ◽  
Vol 79 ◽  
pp. 12-18 ◽  
Author(s):  
Pascual Fernández ◽  
Blas Pelegrín ◽  
Algirdas Lančinskas ◽  
Julius Žilinskas
Keyword(s):  
Heuristic Algorithms ◽  
Customer Behavior ◽  
Location Problems ◽  
Competitive Location

scholarly journals Solving Competitive Location Problems with Social Media Data Based on Customers’ Local Sensitivities

2019 ◽  
Vol 8 (5) ◽  
pp. 202 ◽  
Author(s):  
Wei Jiang ◽  
Yandong Wang ◽  
Mingxuan Dou ◽  
Senbao Liu ◽  
Shiwei Shao ◽  
...  
Keyword(s):  
Social Media ◽  
Cost Effective ◽  
Optimal Location ◽  
Location Based Services ◽  
Location Problems ◽  
Competitive Location ◽  
Test Cases ◽  
Social Media Data ◽  
Location Data ◽  
Media Data

Competitive location problems (CLPs) are a crucial business concern. Evaluating customers’ sensitivities to different facility attractions (such as distance and business area) is the premise for solving a CLP. Currently, the development of location-based services facilitates the use of location data for sensitivity evaluations. Most studies based on location data assumed the customers’ sensitivities to be global and constant over space. In this paper, we proposed a new method of using social media data to solve competitive location problems based on the evaluation of customers’ local sensitivities. Regular units were first designed to spatially aggregate social media data to extract samples with uniform spatial distribution. Then, geographically weighted regression (GWR) and the Huff model were combined to evaluate local sensitivities. By applying the evaluation results, the captures for different feasible locations were calculated, and the optimal location for a new retail facility could be determined. In our study, the five largest retail agglomerations in Beijing were taken as test cases, and a possible new retail agglomeration was located. The results of our study can help people have a better understanding of the spatial variation of customers’ local sensitivities. In addition, our results indicate that our method can solve competitive location problems in a cost-effective way.

ON PLANAR MEDIANOID COMPETITIVE LOCATION PROBLEMS WITH MANHATTAN DISTANCE

2013 ◽  
Vol 30 (02) ◽  
pp. 1250050 ◽  
Author(s):  
KE FU ◽  
ZHAOWEI MIAO ◽  
JIAYAN XU
Keyword(s):  
Polynomial Time ◽  
General Problem ◽  
Location Problem ◽  
Location Problems ◽  
Manhattan Distance ◽  
Competitive Location ◽  
Customer Preferences ◽  
Special Cases ◽  
Present Solution ◽  
Solution Methods

A medianoid problem is a competitive location problem that determines the locations of a number of new service facilities that are competing with existing facilities for service to customers. This paper studies the medianoid problem on the plane with Manhattan distance. For the medianoid problem with binary customer preferences, i.e., a case where customers choose the closest facility to satisfy their entire demand, we show that the general problem is NP-hard and present solution methods to solve various special cases in polynomial time. We also show that the problem with partially binary customer preferences can be solved with a similar approach we develop for the model with binary customer preferences.

scholarly journals Integer programming formulations for three sequential discrete competitive location problems with foresight

2018 ◽  
Vol 265 (3) ◽  
pp. 872-881 ◽  
Author(s):  
José Gentile ◽  
Artur Alves Pessoa ◽  
Michael Poss ◽  
Marcos Costa Roboredo
Keyword(s):  
Integer Programming ◽  
Location Problems ◽  
Competitive Location

An approach for solving competitive location problems with variable demand using multicore systems

2012 ◽  
Vol 8 (2) ◽  
pp. 555-567 ◽  
Author(s):  
A. G. Arrondo ◽  
J. Fernández ◽  
J. L. Redondo ◽  
P. M. Ortigosa
Keyword(s):  
Location Problems ◽  
Competitive Location ◽  
Multicore Systems ◽  
Variable Demand

scholarly journals An Efficient Algorithm for Capacitated Multifacility Location Problems

2007 ◽  
Vol 3 (8) ◽  
pp. 583-591 ◽  
Author(s):  
Chansiri Singhtaun ◽  
Peerayuth Charnsethi
Keyword(s):  
Efficient Algorithm ◽  
Location Problems ◽  
Multifacility Location

Parallel algorithms for continuous competitive location problems

2008 ◽  
Vol 23 (5) ◽  
pp. 779-791 ◽  
Author(s):  
Juana L. Redondo ◽  
José Fernández ◽  
Inmaculada García ◽  
Pilar M. Ortigosa
Keyword(s):  
Parallel Algorithms ◽  
Location Problems ◽  
Competitive Location
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