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From Goal Programming for Continuous Multi-Criteria Optimization to the Target Decision Rule for Mixed Uncertain

Helena Gaspars-Wieloch¹

¹Department of Operations Research and Mathematical Economics, Poznan University of Economics and Business, Al. Niepodleglosci 10, 61-875 Poznań, Poland.

Entropy (Basel, Switzerland)

|January 21, 2022

Summary

This study introduces a new goal programming (GP) decision rule for mixed uncertain problems. This method aids optimists, pessimists, and moderates in making one-shot decisions, even with neutral criteria.

Keywords:

attitude towards risk continuous multi-criteria optimization under certainty game theory goal programming mixed strategies neutral criteria one-criterion uncertain problems scenario planning

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Area of Science:

Operations Research
Decision Science
Optimization Theory

Background:

Goal programming (GP) is a multi-criteria optimization technique.
Recent literature highlights similarities between decision making under certainty and uncertainty.
Existing methods for uncertain decision making have limitations in handling neutral criteria.

Purpose of the Study:

To develop a novel decision rule for mixed uncertain problems using goal programming methodology.
To extend GP applications to a new domain of decision making under uncertainty.
To provide a flexible decision-making tool for various decision-maker profiles (pessimists, optimists, moderates).

Main Methods:

Adaptation of goal programming (GP) methodology.
Development of a new decision rule for mixed uncertain problems.
Application to both discrete and continuous optimization scenarios.

Main Results:

A new decision rule for mixed uncertain problems is created based on GP.
The procedure accommodates different decision-maker attitudes (pessimistic, optimistic, moderate).
The approach allows for the analysis of neutral criteria, an advantage over classical methods.

Conclusions:

The novel GP-based decision rule offers a versatile approach to mixed uncertain problems.
This method enhances decision-making capabilities by incorporating neutral criteria.
The procedure is suitable for one-shot decisions across various decision-maker preferences.