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- Title
Heuristic algorithms for the inverse mixed integer linear programming problem.
- Authors
Zhaoyang Duan; Lizhi Wang
- Abstract
The recent development in inverse optimization, in particular the extension from the inverse linear programming problem to the inverse mixed integer linear programming problem (InvMILP), provides more powerful modeling tools but also presents more challenges to the design of efficient solution techniques. The only reported InvMILP algorithm, referred to as Alg, although finitely converging to global optimality, suffers two limitations that greatly restrict its applicability: it is time consuming and does not generate a feasible solution except for the optimal one. This paper presents heuristic algorithms that are designed to be implemented and executed in parallel with Alg in order to alleviate and overcome its two limitations. Computational experiments show that implementing the heuristic algorithm on one auxiliary processor in parallel with Alg on the main processor significantly improves its computational efficiency, in addition to providing a series of improving feasible upper bound solutions. The additional speedup of parallel implementation on two or more auxiliary processors appears to be incremental, but the upper bound can be improved much faster.
- Subjects
LINEAR programming; INTEGER programming; HEURISTIC algorithms; ALGORITHMS; HEURISTIC; ARTIFICIAL intelligence
- Publication
Journal of Global Optimization, 2011, Vol 51, Issue 3, p463
- ISSN
0925-5001
- Publication type
Article
- DOI
10.1007/s10898-010-9637-2