A framework for robust and flexible optimisation using metaheuristics

This is a summary of the most important results presented in the authors PhD thesis. This thesis, written in English, was defended on 13 June 2003 and supervised by Johan Springael and Gerrit K. Janssens. A copy is available from the author upon request. This PhD thesis focuses on stochastic problems and develops a framework to find robust and flexible solutions of such problems. The framework is applied to several well-known problems in the realm of supply chain design. Besides this framework, the thesis contains several other important contributions. A new type of robustness and flexibility is proposed, that expresses the need for solutions to remain approximately the same when changes occur in the problem data. Several distance measures are developed to calculate the distance (or similarity) between solutions of different permutation type problems. A new type of genetic algorithm is also proposed, that uses a distance measure to maintain a diverse population of high-quality solutions.Received: June 2003