Journal Article10.1057/JORS.1980.95
Multi-Objective Interactive Programming
TL;DR: This paper proposes a method for finding optimal, or near optimal, solutions for problems involving m objective functions, where there is an overall criterion which is a weighted sum of the m Objective functions, but where the weights are, initially, unknown.
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Abstract: This paper proposes a method for finding optimal, or near optimal, solutions for problems involving m objective functions, where there is an overall criterion which is a weighted sum of the m objective functions, but where the weights are, initially, unknown. The process is an interactive one, beginning with a set within which the actual weighting vector is known to lie, and progressively cutting down the size of the set until an acceptable solution is found. A by-product of the procedure is an iterative method for finding the generators of the polyhedral cones, within which the weighting vector must lie, at each stage.
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Citations
An Overview of Techniques for Solving Multiobjective Mathematical Programs
TL;DR: This overview concentrates on those techniques which require an articulation of the decision maker's preference structure either during or after the optimization, since these are the areas where most of the recent research has been conducted.
380
An Interactive Multiple Objective Linear Programming Method for a Class of Underlying Nonlinear Utility Functions
Stanley Zionts,Jyrki Wallenius +1 more
TL;DR: This paper develops a method for interactive multiple objective linear programming assuming an unknown pseudo concave utility function satisfying certain general properties and presents the supporting theory and algorithm.
371
Interactive multiple objective optimization: survey l—continuous case
Wan S. Shin,A. Ravindran +1 more
TL;DR: The interactive methods developed for solving continuous multiple objective optimization problems and their applications are surveyed, based on the nature of preference assessments, functional assumptions and relationships between the methods.
199
Principles of multiobjective optimization
Richard E. Rosenthal
- 01 Aug 1984
TL;DR: In this paper, the authors used the Naval Postgraduate School Foundation (NPSF) Research Program under contract with the National Research Council (NRC) to support the development of a neural network.
97
Interactive Multi-Objective Programming: Its Aims, Applications and Demands
TL;DR: The underlying rationale of a family of methods known collectively as interactive multi-objective programming is presented, albeit as seen by a devil's advocate, but the validity of these methods is questioned because their assumptions are not supported by the empirical results of behavioural decision theory.
62
References
A Weighted Maximin and Maximax Approach to Multiple Criteria Decision Making
TL;DR: In this paper, a Weighted Maximin and Maximax approach to multiple criteria decision making is presented, which is based on the MMD approach to decision-making in the field of operational research.
20
Interactive approach for multi-criterion optimization, with an application to the operation of an academic department.
TL;DR: An interactive mathematical programming approach to multi-criterion optimization is developed, and then illustrated by an application to the aggregated operating problem of an academic department.