2009
DOI: 10.1016/j.ejor.2009.01.061
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Tradeoff-based decomposition and decision-making in multiobjective programming

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Cited by 9 publications
(4 citation statements)
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“…Our main contribution is a scheme that retains the quality of the best previous algorithm while achieving a more benign ratio between computational effort and problem dimension. The presented algorithm also generalizes sandwich algorithms to be compatible with cone-based preference models (see, e.g., Engau 2009, Hunt and Wiecek 2003, Monz 2006. Ordering cones have proven useful in multicriteria IMRT planning for excluding parts of the Pareto surface that are known a priori not to be of interest (Serna et al 2009).…”
Section: Introductionmentioning
confidence: 94%
“…Our main contribution is a scheme that retains the quality of the best previous algorithm while achieving a more benign ratio between computational effort and problem dimension. The presented algorithm also generalizes sandwich algorithms to be compatible with cone-based preference models (see, e.g., Engau 2009, Hunt and Wiecek 2003, Monz 2006. Ordering cones have proven useful in multicriteria IMRT planning for excluding parts of the Pareto surface that are known a priori not to be of interest (Serna et al 2009).…”
Section: Introductionmentioning
confidence: 94%
“…A metric has to be specific for an industry and an objective, but if there are different objectives to take into consideration to facilitate trade-offs between different points of view (disciplines, designers, services), the metric building process is the same for each metric, and a lot of multi-objective optimization techniques [48][49] [50], or techniques based on weighting considerations can be used to achieve an optimal global metric.…”
Section: Discussion and Future Workmentioning
confidence: 99%
“…Finally, the last group of MOP problems provides solutions based on a continuous interaction with DM and tries to reach the preferred solution at the end of the algorithm. Based on this sound idea, there are many developed methods categorized in this group [13][14][15][16][17][18][19][20][21]. Different procedures may be better suited for different types of decision makers, for different types of decision situations, or for different stages in the decision making process [22].…”
Section: Introductionmentioning
confidence: 99%
“…The interaction with DM proceeds by generating smaller subsets of the efficient set until a final solution is located [19]. The proposed method by Engau [14] decomposes the original MOP problem into a collection of smaller-sized subproblems to facilitate the evaluation of tradeoffs and the articulation of preferences. A priori preferences on objective tradeoffs are integrated into this process, and DM is supported by an interactive procedure to coordinate any remaining tradeoffs.…”
Section: Introductionmentioning
confidence: 99%