A multi-objective evolutionary algorithm with mutual-information-guided improvement phase for feature selection in complex manufacturing processes

An-Da Li, Zhen He, Qing Wang, Yang Zhang and Yanhui Ma

European Journal of Operational Research, 2025, vol. 323, issue 3, 952-965

Abstract: Complex manufacturing processes (CMP) involve numerous features that impact product quality. Therefore, selecting key process features (KPF) is crucial for effective quality prediction and control in CMPs. This paper proposes a KPF (feature) selection method for the high-dimensional CMP data. The KPF selection problem is formulated as a bi-objective combinatorial optimization task of maximizing the geometric mean measure and minimizing the number of selected features. To solve this challenging high-dimensional KPF selection problem, we propose a novel multi-objective evolutionary algorithm (MOEA) called NSGAII-MIIP. NSGAII-MIIP applies an improvement phase (called MIIP) to purify the non-dominated solutions obtained by genetic operators during the iteration process to improve the FS performance. The improvement phase is guided by a mutual-information-based feature importance measure considering both a feature’s relevance degree to class (product quality level) and its redundancy degree to selected features. This allows MIIP to efficiently update non-dominated solutions by selecting relevant features and eliminating redundant features. Moreover, MIIP is seamlessly integrated into the solution ranking process of NSGAII-MIIP so that solutions from the improvement phase can be ranked together with original solutions in the population efficiently. Experiments on eight datasets show that NSGAII-MIIP has better KPF selection performance than eight state-of-the-art multi-objective FS methods. Moreover, NSGAII-MIIP exhibits superior search performance compared to eight typical multi-objective optimization algorithms.

Keywords: Evolutionary computations; Multi-objective optimization; Feature selection; Improvement phase; Quality prediction (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:323:y:2025:i:3:p:952-965

DOI: 10.1016/j.ejor.2024.12.036

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