Improved feasible value constraint for multiobjective optimization problems

Document Type : Research Article

Authors

Department of Mathematics, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

Abstract

 In this paper, we focus on the utilization of the feasible value constraint technique to address multiobjective optimization problems (MOPs). It is attempted to overcome certain drawbacks associated with this method, such as restrictions on functions and weights, inflexibility in constraints, and challenges in assessing proper efficiency. To accomplish this, we propose an improved version of the feasible value constraint technique. Then, by incorporating approximate solutions, we establish connections between $\varepsilon$-(weakly, properly) efficient points in a general MOP and $\epsilon$-optimal solutions to the scalarization problem.

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References

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Journal of Mathematical Modeling
Volume 13, Issue 1
March 2025
Pages 105-120

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