Multicriteria Optimization (2. ed.)

By Matthias Ehrgott. 2005

908 citations recorded by the source corpus.

Subfields: Industrial and Manufacturing Engineering

Citations in the corpus

• Learning Fair Rule Lists (2019, neutral): “aving the best value for this objective function. However, in many applications, one has to consider the concurrent optimization of several objective functions. A multi-objective optimization problem [15, 22] can be defined as follows: Definition 2.2 (Multi-objective optimization problem). minimize ”
• Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation (2015, neutral): “es of Np, the number of proposals from each ranked list Ni such that the joint pool of p proposals has the best achievable quality. We frame this learning problem as a Pareto front optimization [39], [40] with two conflicting objective functions: number of proposals and achievable quality. At test ti”
• Linear Fitted-Q Iteration with Multiple Reward Functions (2012, neutral): “…concep- LIZOTTE, BOWLING AND MURPHY tual and computational insight that is well-established in the multi-criterion optimization literature (Ehrgott, 2005): the set of actions that are optimal for some δ ∈ [0] [1] are exactly those actions whose line-representations lie on the upper convex…”
• Efficient Reinforcement Learning with Multiple Reward Functions for Randomized Controlled Trial Analysis (2010, neutral): “…representations offer an important conceptual and computational insight that is well-established in the multi-criterion optimization literature (Ehrgott, 2005): The set of actions that are optimal for some δ ∈ [0, 1] are exactly those actions whose line-representations lie on the upper convex…”
• A tutorial on multiobjective optimization: fundamentals and evolutionary methods (2018, neutral): “For the notions we discuss in this section a good reference is Ehrgott (2005).”
• Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions (2005, neutral): “Although multicriteria ratings have not yet been examined in the recommender systems literature, they have been extensively studied in the Operations Research community [33], [102].”
• Comparison of different multi-objective calibration criteria using a conceptual rainfall-runoff model of flood events. (2007, neutral): “Over the last three decades tremendous amount of re- search effort has been expanded on multi-objective decision making leading to the publication of many interesting results in the literature (Changkong and Haimes, 1983; Miettinen, 1999; Ehrgott, 2005).”