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A new local search for continuous location problems |
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| Authors: | Jack Brimberg Zvi Drezner Nenad Mladenović Said Salhi |
| Institution: | 1. Department of Mathematics and Computer Science, Royal Military College of Canada, Kingston, ON K7K 7B4, Canada;2. Steven G. Mihaylo College of Business and Economics, California State University, Fullerton, CA 92634, USA;3. Department of Mathematical Sciences, School of Information Systems, Computing and Mathematics, University of Brunel, Uxbridge, Middlesex UB8 3PH, United Kingdom;4. Centre for Logistics & Heuristic Optimization, Kent Business School, University of Kent, Canterbury CT2 7PE, United Kingdom |
| Abstract: | This paper presents a new local search approach for solving continuous location problems. The main idea is to exploit the relation between the continuous model and its discrete counterpart. A local search is first conducted in the continuous space until a local optimum is reached. It then switches to a discrete space that represents a discretisation of the continuous model to find an improved solution from there. The process continues switching between the two problem formulations until no further improvement can be found in either. Thus, we may view the procedure as a new adaption of formulation space search. The local search is applied to the multi-source Weber problem where encouraging results are obtained. This local search is also embedded within Variable Neighbourhood Search producing excellent results. |
| Keywords: | Continuous location Weber problem Space search formulation Variable neighbourhood |
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