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Alternating Refined Constraint Method: A Multi-Objective Solution Approach for Energy Systems Optimization
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DOI：10.1109/tpwrs.2026.3682532.png)
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Abstract
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This paper proposes an alternating refined constraint method (ARCM) for solving multi-objective optimization problems (MOPs) in energy systems. Through a two-stage solution mechanism, ARCM addresses a critical theoretical shortcoming of prevailing methods, which may occasionally yield weakly Pareto optimal solutions when tackling non-convex problems involving binary variables and nonlinear constraints. ARCM utilizes a two-stage solution strategy to clarify the decision-making logic for energy systems optimization and mathematically guarantees that every generated solution satisfies strong Pareto optimality. Simulation results show the effectiveness of the method, and a comparison with other multi-objective solution methods is made.
Keywords:
Multi-objective optimization
Pareto front
alternating refined constraint method
$\varepsilon$ -constraint method
non-convex optimization
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7.2
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1.1W
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5.0W
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