The ε constraint method is an important technique for handling constraints in constrained optimization problems. The proper selection of ε is highly dependent on the population distribution in each generation, making it exceedingly difficult to derive an analytical expression for ε . Consequently, this nonlinear dependency inevitably compromises the performance of conventional ε -constraint methods. To tackle this issue, we incorporate the concept of variable universes of discourse into a fuzzy logic controller. In this paper, we propose a variable-universe fuzzy logic controller (C-VUFC) to adaptively determine ε . By exploiting fuzzy if-then rules and membership functions, the proposed controller explicitly models the inherently nonlinear relationship between ε and the population distribution. Furthermore, we develop a domain adaptation mechanism that dynamically adjusts the universes of discourse based on historical constraint violation trends, thereby improving the adaptability of ε selection. Therefore, the proposed approach outperforms existing methods. Two novel algorithms are designed by integrating the proposed controller. The proposed algorithms are compared with state-of-the-art algorithms and the results demonstrate their effectiveness.
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