A Problem-Specific and Effective Metaheuristic for Flexibility Design
Michael Schneider (TU Kaiserslautern), Jörn Grahl (Johannes Gutenberg Universität Mainz), David Francas (Universität Mannheim):
Abstract
Matching uncertain demand with capacities is notoriously hard. Operations
managers can use mix-flexible resources to shift excess demands to unused capacities.
To find the optimal configuration of a mix-flexible production network, a
flexibility design problem (FDP) is solved. Existing literature on FDPs provides
qualitative structural insights, but work on solution methods is rare. We contribute
the first metaheuristic which integrates these structural insights and is specifically
tailored to solve FDPs. Our genetic algorithm is compared to commercial solvers on
instances of up to 15 demand types, resources, and 500 demand scenarios. Experimental
evidence shows that in the realistic case of flexible optimal configurations,
it dominates the comparison methods regarding runtime and solution quality.
managers can use mix-flexible resources to shift excess demands to unused capacities.
To find the optimal configuration of a mix-flexible production network, a
flexibility design problem (FDP) is solved. Existing literature on FDPs provides
qualitative structural insights, but work on solution methods is rare. We contribute
the first metaheuristic which integrates these structural insights and is specifically
tailored to solve FDPs. Our genetic algorithm is compared to commercial solvers on
instances of up to 15 demand types, resources, and 500 demand scenarios. Experimental
evidence shows that in the realistic case of flexible optimal configurations,
it dominates the comparison methods regarding runtime and solution quality.
University of Mainz Discussion Paper Series, Link
08.04.2010 | Forschungsarbeit