On the Use of Preferential Weights in Interactive Reference Point Based Methods

DOI10.1007/978-3-540-85646-7_20zbMath1176.90549OpenAlexW130797717WikidataQ109314894 ScholiaQ109314894MaRDI QIDQ3649611

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Publication date: 4 December 2009

Published in: Multiobjective Programming and Goal Programming (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-85646-7_20

zbMATH Keywords

multiobjective programmingmultiobjective optimizationpreferencesmultiple objectivesinteractive methodsreference point methods

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29)

Related Items (7)

An exact scalarization method with multiple reference points for bi-objective integer linear optimization problems ⋮ A synchronous reference point-based interactive method for stochastic multiobjective programming ⋮ Global formulation for interactive multiobjective optimization ⋮ A new achievement scalarizing function based on parameterization in multiobjective optimization ⋮ Improving convergence of evolutionary multi-objective optimization with local search: a concurrent-hybrid algorithm ⋮ INTEREST: A reference-point-based interactive procedure for stochastic multiobjective programming problems ⋮ Incorporating preferential weights as a benchmark into a sequential reference point method

Cites Work

• Unnamed Item
• Unnamed Item
• A visual interactive method for solving the multiple criteria problem
• Nonlinear multiobjective optimization
• The ``Light Beam Search approach. -- An overview of methodology and applications
• On scalarizing functions in multiobjective optimization
• Experiments with classification-based scalarizing functions in interactive multiobjective optimization
• Synchronous approach in interactive multiobjective optimization
• Comparative evaluation of some interactive reference point-based methods for multi-objective optimisation
• A mathematical basis for satisficing decision making
• A naïve approach for solving MCDM problems: the GUESS method
• Integration of Two Multiobjective Optimization Methods for Nonlinear Problems
• Interactive bundle-based method for nondifferentiable multiobjeective optimization: nimbus^§
• Linear programming with multiple objective functions: Step method (stem)

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