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This document presents an adaptive collaborative multi-objective evolutionary algorithm (ACMOEA) designed to optimize hybrid flow shop scheduling problems that involve group setup times and consistent sublots, particularly in printed circuit board assembly. The algorithm aims to minimize makespan and energy consumption while ensuring sublot consistency, demonstrating superior performance compared to existing methods in terms of solution efficiency and convergence. The study highlights the complexity of the

Author

Achraf Sayah

Language

EN