Mixed Integer Program Heuristic for Linear Ordering Problem
Ehsan Iranmanesh, Ramesh Krishnamurti
2016
Abstract
The Linear Ordering Problem is a classic optimization problem which can be used to model problems in graph theory, machine scheduling, and voting theory, many of which have practical applications. Relatively recently, there has been some success in using Mixed Integer Program (MIP) heuristic for NP-hard optimization problems. We report our experience with using a MIP heuristic for the problem. Our heuristic generates a starting feasible solution based on the Linear Programming solution to the IP formulation for the Linear Ordering Problem. For each starting solution, a neighborhood is defined, again based on the LP solution to the problem. A MIP solver is then used to obtain the optimal solution among all the solutions in the neighborhood. The MIP heuristic shows promise for large problems of hard instances.
References
- Ahuja, R. K., Ergun, O., Orlin, J. B., and Punnen, A. P. (2002). A survey of very large-scale neighborhood search techniques. Discrete Applied Mathematics, 123(1-3):75 - 102.
- Applegate, D., Bixby, R., Chvatal, V., and Cook, W. (1999). Finding tours in the traveling salesman problem. Technical report, Forschungsinstitut fur Diskrete Mathematik, University of Bonn, Germany.
- Burke, E. K., Cowling, P. I., and Keuthen, R. (2000). Embeded local search and variable neighborhood search heuristics applied to the travelling salesman problem. Technical report, University of Nottingham.
- Burke, E. K., Cowling, P. I., and Keuthen, R. (2001). Effective local and guided variable neighbourhood search methods for the asymmetric travelling salesman problem. In Proceedings of the EvoWorkshops on Applications of Evolutionary Computing, pages 203-212, London, UK, UK. Springer-Verlag.
- Dumitrescu, I. and Stutzle, T. (2003). Combinations of local search and exact algorithms. In Applications of Evolutionary Computation, pages 211-223. Springer.
- Fischetti, M. and Lodi, A. (2003). Local branching. Math. Program., 98(1-3):23-47.
- Garey, M. R. and Johnson, D. S. (1979). Computers and Intractability: A Guide to the Theory of NPCompleteness. W. H. Freeman and Company.
- Lin, S. (1965). Computer solutions of the traveling salesman problem. 44(10):2245-2269.
- Loureno, H. R. (1995). Job-shop scheduling: Computational study of local search and large-step optimization methods. European Journal of Operational Research, 83(2):347 - 364. EURO Summer Institute Combinatorial Optimization.
- Maniezzo, V. (1999). Exact and approximate nondeterministic tree-search procedures for the quadratic assignment problem. INFORMS Journal on Computing, 11(4):358-369.
- Marti, R. and Reinelt, G. (2011). The Linear Ordering Problem: Exact and Heuristic Methods in Combinatorial Optimization. Applied Mathematical Sciences Volume 175. Springer.
- Marti, R., Reinelt, G., and Duarte, A. (2009). Optisicom project. http: www.optsicom.es/lolib.
Paper Citation
in Harvard Style
Iranmanesh E. and Krishnamurti R. (2016). Mixed Integer Program Heuristic for Linear Ordering Problem . In Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-171-7, pages 152-156. DOI: 10.5220/0005710701520156
in Bibtex Style
@conference{icores16,
author={Ehsan Iranmanesh and Ramesh Krishnamurti},
title={Mixed Integer Program Heuristic for Linear Ordering Problem},
booktitle={Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2016},
pages={152-156},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005710701520156},
isbn={978-989-758-171-7},
}
in EndNote Style
TY - CONF
JO - Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Mixed Integer Program Heuristic for Linear Ordering Problem
SN - 978-989-758-171-7
AU - Iranmanesh E.
AU - Krishnamurti R.
PY - 2016
SP - 152
EP - 156
DO - 10.5220/0005710701520156