Using injection points in reformulation local search for solving continuous location problems

Reformulation local search (RLS) has been recently proposed as a new approach for solving continuous location problems. The main idea, although not new, is to exploit the relation between the continuous model and its discrete counterpart. The RLS switches between the continuous model and a discrete...

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Bibliographic Details
Main Authors: Brimberg Jack, Drezner Zvi, Mladenović Nenad, Salhi Said
Format: Article
Language:English
Published: University of Belgrade 2017-01-01
Series:Yugoslav Journal of Operations Research
Subjects:
Online Access:http://www.doiserbia.nb.rs/img/doi/0354-0243/2017/0354-02431600018B.pdf
Description
Summary:Reformulation local search (RLS) has been recently proposed as a new approach for solving continuous location problems. The main idea, although not new, is to exploit the relation between the continuous model and its discrete counterpart. The RLS switches between the continuous model and a discrete relaxation in order to expand the search. In each iteration new points obtained in the continuous phase are added to the discrete formulation. Thus, the two formulations become equivalent in a limiting sense. In this paper we introduce the idea of adding 'injection points' in the discrete phase of RLS in order to escape a current local solution. Preliminary results are obtained on benchmark data sets for the multi-source Weber problem that support further investigation of the RLS framework.
ISSN:0354-0243
1820-743X