Algorithms for a 2-stage hybrid flow shop scheduling problem with two classes of jobs

초록

This study addresses the complex 2-stage hybrid flow shop (HFS) scheduling problem, which involves urgent and normal jobs in a multi-agent context. The goal is to simultaneously minimize the makespan for normal jobs and the total tardiness for urgent jobs. Our proposed approaches include a Mixed-Integer Programming (MIP) model, list scheduling algorithms (MEDD, MEDD2), constructive algorithms (MNEH, MN-NEH, MFL, MN-MFL), and a simulated annealing (SA) metaheuristic to find practical solutions. Extensive experiments, using randomly generated instances which reflect real manufacturing environments, validate the algorithms' performance. The SA algorithm consistently exhibits a superior and robust performance across all scenarios, finding solutions remarkably close to the optimal. Additionally, MFL and MN-MFL show noteworthy efficiencies and stable performances, indicating their potential for practical applications in rapid decision-making environments.

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