Discrete Facility Location Problems

There are a variety of discrete facility location models that have practical relevance for operations management and management science courses. Integer linear programming (ILP) is the standard technique for solving such problems. An alternative approach that is often conceptually appealing to students is to pose the problem as one of finding the best possible subset of p facilities out of n possible candidates. I developed an Excel workbook that allows students to interactively evaluate the quality of different subsets, to run a VBA macro that finds the optimal subset, or to solve an ILP formulation that finds the optimal subset. Spreadsheets are available for five classic discrete location models: (1) the location set-covering problem, (2) the maximal covering location problem, (3) the p-median problem, (4) the p-centers problem, and (5) the simple plant location problem. The results from an assignment in a master’s-level business analytics course indicate that the workbook facilitates a better conceptual understanding of the precise nature of the discrete facility location problems by showing that they can be solved via enumeration of all possible combinations of p subsets that can be drawn from n candidate locations. More important, students directly observe the superiority of ILP as a solution approach as n increases and as p approaches n/2.

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Metaheuristic applications on discrete facility location problems: a survey

OPSEARCH ◽

10.1007/s12597-014-0190-5 ◽

2014 ◽

Vol 52 (3) ◽

pp. 530-561 ◽

Cited By ~ 20

Author(s):

Sumanta Basu ◽

Megha Sharma ◽

Partha Sarathi Ghosh

Keyword(s):

Facility Location ◽

Location Problems ◽

Facility Location Problems ◽

Discrete Facility Location

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GIS and geometric representation in facility location problems

International Journal of Geographical Information Systems ◽

10.1080/026937996137729 ◽

1996 ◽

Vol 10 (7) ◽

pp. 791-816

Author(s):

Harvey J. Miller

Keyword(s):

Facility Location ◽

Location Problems ◽

Geometric Representation ◽

Facility Location Problems

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Conditional Facility Location Problems with Continuous Demand and a Polygonal Barrier

European Journal of Operational Research ◽

10.1016/j.ejor.2021.02.032 ◽

2021 ◽

Author(s):

Thomas Byrne ◽

Jörg Kalcsics

Keyword(s):

Facility Location ◽

Location Problems ◽

Facility Location Problems ◽

Continuous Demand

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Integration of AHP-QFD for selecting facility location

Benchmarking An International Journal ◽

10.1108/bij-06-2013-0064 ◽

2015 ◽

Vol 22 (3) ◽

pp. 411-425 ◽

Cited By ~ 12

Author(s):

Rajesh Chadawada ◽

Ahmad Sarfaraz ◽

Kouroush Jenab ◽

Hamid Pourmohammadi

Keyword(s):

Facility Location ◽

Solution Process ◽

Pairwise Comparison ◽

Integrated Approach ◽

Point Of View ◽

Location Problems ◽

Analytic Hierarchy ◽

Content Type ◽

Facility Location Problems ◽

Managerial Experience

Purpose – The purpose of this paper is to describe and implements an analytic hierarchy process (AHP)-QFD model for selecting the best location from an organization point of view which picks the site with the best opportunity requirements. Integration of AHP-QFD process gives us a new approach to assist organizations through observing various factors and selecting the best location among different alternatives. This approach uses AHP method to match the preferences required by decision makers and these preferences are applied to the characteristics of QFD. The model fundamental requirement are perfect potential locales and the areas are contrasted and both quantitative and qualitative elements to permit directors to join managerial experience and judgment in the answer process. The AHP-QFD model is also applied on a case study to illustrate the solution process. Design/methodology/approach – The integration of AHP and QFD is used to analyze available options and select the best alternative. This can be done by ranking each criterion through a pairwise comparison. Given collected data, the QFD approach is used to find the capability of each criterion. Findings – Integration of AHP-QFD is used to select the best alternative in facility location. This integrated approach can be best used in dealing with facility location problems. Originality/value – The developed AHP-QFD model in facility location problems, facilitates the inclusion of market criteria and decision maker opinion into the traditional cost function, which has been mainly distance base in the literature.

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