Optimization-based decision support systems for multiobjective decision making

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Decision making, one of the most important human activities, is ever more difficult in today's complex and rapidly changing environment. In many industrial sectors, managers have to face increasingly complex problems which often involve the simultaneous optimization of multiple incommensurable and often competing objectives. Decision Support Systems (DSS) are therefore playing an ever more important role in organizational decision making for business intelligence in all disciplines. Moreover, combining artificial intelligence and operations research techniques to tackle large problems can also benefit the development of DSS.**The principal objective of the proposed research program is to develop efficient and flexible optimization tools as the main component of DSS in order to solve industrial problems. The principal application used to measure the pertinence and performance of solution strategies is production scheduling. This research has three orientations: (1) modeling complex problems, especially by the simultaneous optimization of several contradictory objectives, in order to enrich the theory but also to develop useful tools; (2) developing and implementing efficient, practical and specifically designed algorithms to solve difficult optimization problems: nature-inspired algorithms are favored here because of their proven record in flexibility and performance over several decades; (3) advancing computational methods, specifically for optimization-based decision support systems on parallel and distributed computer architectures, in order to obtain reductions in execution time but also to improve solution quality.************