Parallel Machine Scheduling withStochastic Workforce Skill Requirements - Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems Access content directly
Conference Papers Year : 2021

Parallel Machine Scheduling withStochastic Workforce Skill Requirements

Xin Liu
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  • PersonId : 1235648
Ming Liu
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  • PersonId : 1235632

Abstract

In the context of Industry 4.0, both of the ability to handle unexpected events and personalization customization are emphasized. This work investigates a parallel machine scheduling problem with uncertain skill requirements. The problem involves a two-stage decision-making process: (i) determining the workers’ skill training plan and the number of opened machines on the first stage before the realization of uncertain skill requirements, and (ii) scheduling jobs and assigning workers to jobs on the second stage, under known skill requirements. The objective is to minimize the expected total cost, including the workers’ skill training cost, machine opening cost and the expected penalty cost of jobs’ tardiness. A two-stage stochastic programming formulation is proposed, and an illustrative example shows the applicability of the model.
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hal-04022140 , version 1 (09-03-2023)

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Xin Liu, Ming Liu. Parallel Machine Scheduling withStochastic Workforce Skill Requirements. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.258-265, ⟨10.1007/978-3-030-85906-0_29⟩. ⟨hal-04022140⟩
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