Estimating aspiration levels from discrete choices -- computational techniques and experiences

DOI10.1016/0377-2217(94)90280-1zbMath0810.90080OpenAlexW2014292685MaRDI QIDQ1333495

Rudolf Vetschera

Publication date: 17 April 1995

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0377-2217(94)90280-1

zbMATH Keywords

multiple criteriamixed integer linear programminginteractive systems

Mathematics Subject Classification ID

Mixed integer programming (90C11) Management decision making, including multiple objectives (90B50)

Related Items (1)

An expert system for multiobjective decision making: Application of fuzzy linguistic preferences and goal programming

Uses Software

• GAMS
• UTA Plus

Cites Work

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• Interactive multiple objective optimization: Survey. I: Continuous case
• The role of weights and scales in the application of multiobjective decision making
• Analysis of multicriteria decision aid in Europe
• On the completeness and constructiveness of parametric characterizations to vector optimization problems
• Multicriteria analysis: Survey and new directions
• Assessing a set of additive utility functions for multicriteria decision- making, the UTA method
• Proper efficiency in nonconvex vector-maximization-problems
• Estimating the weights for multiple attributes in a composite criterion using pairwise judgments
• Optimal Estimation of Executive Compensation by Linear Programming
• Solving the Discrete Multiple Criteria Problem using Convex Cones
• Estimation of Attribute Weights from Preference Comparisons
• An Overview of Techniques for Solving Multiobjective Mathematical Programs
• Mixed-Integer Linear-Programming Formulation of a Multi-Attribute Threshold Model of Choice
• A Method of Multiattribute Decision Making with Incomplete Information
• `` Direct Search Solution of Numerical and Statistical Problems
• Identifying and ranking a most preferred subset of alternatives in the presence of multiple criteria

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