Inverse optimization for multi-objective linear programming Review
| Authors: | Naghavi, M.; Foroughi, A. A.; Zarepisheh, M. |
| Review Title: | Inverse optimization for multi-objective linear programming |
| Abstract: | This paper generalizes inverse optimization for multi-objective linear programming where we are looking for the least problem modifications to make a given feasible solution a weak efficient solution. This is a natural extension of inverse optimization for single-objective linear programming with regular “optimality” replaced by the “Pareto optimality”. This extension, however, leads to a non-convex optimization problem. We prove some special characteristics of the problem, allowing us to solve the non-convex problem by solving a series of convex problems. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature. |
| Keywords: | problem solving; efficiency; inverse problems; inverse optimization; multiobjective optimization; nonconvex optimization; convex optimization; linear programming; multi-objective linear programming; pareto principle; feasible solution; natural extension; nonconvex problem; pareto-optimality; weak efficient solutions |
| Journal Title: | Optimization Letters |
| Volume: | 13 |
| Issue: | 2 |
| ISSN: | 1862-4472 |
| Publisher: | Springer |
| Date Published: | 2019-03-01 |
| Start Page: | 281 |
| End Page: | 294 |
| Language: | English |
| DOI: | 10.1007/s11590-019-01394-0 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Source: Scopus |
