Robust optimization of a bi‑objective tactical resource allocation problem with uncertain qualification costs
Journal article, 2022

In the presence of uncertainties in the parameters of a mathematical model, optimal solutions using nominal or expected parameter values can be misleading. In practice, robust solutions to an optimization problem are desired. Although robustness is a key research topic within single-objective optimization, little attention is received within multi-objective optimization, i.e. robust multi-objective optimization. This work builds on recent work within robust multi-objective optimization and presents a new robust efficiency concept for bi-objective optimization problems with one uncertain objective. Our proposed concept and algorithmic contribution are tested on a real-world multi-item capacitated resource planning problem, appearing at a large aerospace company manufacturing high precision engine parts. Our algorithm finds all the robust efficient solutions required by the decision-makers in significantly less time than the approach of Kuhn et al. (Eur J Oper Res 252(2):418–431, 2016) on 28 of the 30 industrial instances.

Bi-objective mixed-integer programming

Robust optimization

Capacity planning

Decision support system

Robust efficient (RE) solutions

Author

Sunney Fotedar

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

University of Gothenburg

Ann-Brith Strömberg

University of Gothenburg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Edvin Åblad

University of Gothenburg

Fraunhofer-Chalmers Centre

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Torgny Almgren

GKN Aerospace Sweden

Autonomous Agents and Multi-Agent Systems

1387-2532 (ISSN) 1573-7454 (eISSN)

Vol. 36 2 36

Tactical resource allocation for efficient capacity Utilization

VINNOVA (2017-04845), 2017-11-10 -- 2022-12-31.

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Other Mathematics

Discrete Mathematics

Areas of Advance

Transport

Production

Roots

Basic sciences

DOI

10.1007/s10458-022-09564-8

More information

Latest update

1/10/2023