Projects per year
Abstract
The discrete α -neighbor p -center problem (d- α - p CP) is an emerging variant of the classical p -center problem which recently got attention in literature. In this problem, we are given a discrete set of points and we need to locate p facilities on these points in such a way that the maximum distance between each point where no facility is located and its α -closest facility is minimized. The only existing algorithms in literature for solving the d- α - p CP are approximation algorithms and two recently proposed heuristics. In this work, we present two integer programming formulations for the d- α - p CP, together with lifting of inequalities, valid inequalities, inequalities that do not change the optimal objective function value and variable fixing procedures. We provide theoretical results on the strength of the formulations and convergence results for the lower bounds obtained after applying the lifting procedures or the variable fixing procedures in an iterative fashion. Based on our formulations and theoretical results, we develop branch-and-cut (B&C ) algorithms, which are further enhanced with a starting heuristic and a primal heuristic. We evaluate the effectiveness of our B&C algorithms using instances from literature. Our algorithms are able to solve 116 out of 194 instances from literature to proven optimality, with a runtime of under a minute for most of them. By doing so, we also provide improved solution values for 116 instances.
| Original language | English |
|---|---|
| Pages (from-to) | 371-399 |
| Number of pages | 29 |
| Journal | Networks |
| Volume | 82 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Dec 2023 |
Fields of science
- 101015 Operations research
- 101016 Optimisation
- 102 Computer Sciences
- 502 Economics
- 502028 Production management
- 502017 Logistics
- 502037 Location planning
- 502050 Business informatics
JKU Focus areas
- Digital Transformation
- Sustainable Development: Responsible Technologies and Management
Projects
- 1 Finished
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MOSOPT - Solving Multi-Objective Facility Layout Problems via Semidefinite Optimization
Gaar, E. (Researcher) & Parragh, S. (PI)
02.05.2022 → 01.05.2024
Project: Funded research › Federal / regional / local authorities