A generalized behavioral-based goal programming approach for decision-making under imprecision
The body of literature on goal programming (GP) approaches in modeling preferences and the satisfaction philosophy in multi-objective programming (MOP) decision-making processes is extensive. However, there has been little focus on how preferences change in relation to the decision-maker's (DM)...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Operations Research Perspectives |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214716024000204 |
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| Summary: | The body of literature on goal programming (GP) approaches in modeling preferences and the satisfaction philosophy in multi-objective programming (MOP) decision-making processes is extensive. However, there has been little focus on how preferences change in relation to the decision-maker's (DM) behavior within this satisfaction philosophy, particularly in situations involving risk. To address this challenge, we propose introducing a behavior-type utility function into the GP model using the concept of a behavior function. This idea offers an innovative perspective for modeling DM's behavioral preferences in the imprecise GP approach by integrating a risk-aversion parameter specific to each objective. We then formulate a generalized behavioral-based GP approach for decision-making based on this new behavior-type utility function. To validate our proposed approach, we present an illustrative example of project selection in health service institutions, followed by a sensitivity analysis and comparisons with other approaches. The results demonstrate that DM's behavioral preferences significantly impact the decision-making process, and the proposed model provides more reasonable and convenient decisions for DMs with varying degrees of risk aversion. |
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| ISSN: | 2214-7160 |