On an instance of the inverse shortest paths problem
Mathematical Programming: Series A and B
The Complexity Analysis of the Inverse Center Location Problem
Journal of Global Optimization
Operations Research
Inverse optimization in high-speed networks
Discrete Applied Mathematics - Special issue: Algorithmic aspects of communication
Constrained Inverse Minimum Spanning Tree Problems under the Bottleneck-Type Hamming Distance
Journal of Global Optimization
Operations Research Letters
Cutting plane algorithms for the inverse mixed integer linear programming problem
Operations Research Letters
Branch-and-bound algorithms for the partial inverse mixed integer linear programming problem
Journal of Global Optimization
Hi-index | 0.00 |
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 AlgInvMILP, 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 AlgInvMILP in order to alleviate and overcome its two limitations. Computational experiments show that implementing the heuristic algorithm on one auxiliary processor in parallel with AlgInvMILP 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.