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Discrete Energy Laws for the First-Order System Least-Squares Finite-Element Approach Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Development of Threshold Algorithms for a Location Problem with Elastic Demand

Authors : Tatyana Levanova, Alexander Gnusarev

Published in: Large-Scale Scientific Computing

Publisher: Springer International Publishing

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Abstract

This work is devoted to development of threshold algorithms for one static probabilistic competitive facility location and design problem in the following formulation. New Company plans to enter the market and to locate new facilities with different design scenarios. Clients of each point choose to use the facilities of Company or its competitors depending on their attractiveness and distance. The aim of the new Company is to capture the greatest number of customers thus serving the largest share of the demand. This share for the Company is elastic and depends on clients’ decisions. We offer three types of threshold algorithms: Simulated annealing, Threshold improvement and Iterative improvement. Experimental tuning of parameters of algorithms was carried out. A comparative analysis of the algorithms, depending on the nature and value of the threshold on special test examples up to 300 locations is carried out. The results of numerical experiments are discussed.

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previous chapter A Non-dominated Sorting Approach to Bi-objective Optimisation of Mixed-Model Two-Sided Assembly Lines
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Metadata
Title
Development of Threshold Algorithms for a Location Problem with Elastic Demand
Authors
Tatyana Levanova
Alexander Gnusarev
Copyright Year
2018
Book
Large-Scale Scientific Computing

Print ISBN: 978-3-319-73440-8

Electronic ISBN: 978-3-319-73441-5

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-73441-5_41

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