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Bibliographic Details
Main Authors: Terrien, Tanguy, Briand, Cyrille
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2605.20387
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author Terrien, Tanguy
Briand, Cyrille
author_facet Terrien, Tanguy
Briand, Cyrille
contents Optimizing schedules in real-world settings often requires considering workload constraints, specially for human resources, to ensure regulatory compliance, impose rest periods, or level the workload over the working horizon. This paper focuses on tackling this family of constraints in the context of preemptive jobshop scheduling, as preemption is particularly relevant when human resources are involved (allowing personnel to flexibly switch between tasks). Preemption also offers theoretical insights as a relaxation of non-preemptive problems. The main contribution of this paper is a Constraint Programming approach designed to handle effectively maximum workload constraints in a preemptive setting, without decomposing activities into unit-duration tasks (which may be computationally prohibitive). Since workload constraints introduce significant additional complexity, we further propose a method that iteratively introduces the workload constraints into the problem, along with tailored heuristics specifically designed to guide the search efficiently. The experimental results demonstrate the effectiveness of our approach on a large set of instances, highlighting its performance compared to a well-known industrial solver, IBM's CP Optimizer.
format Preprint
id arxiv_https___arxiv_org_abs_2605_20387
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle An iterative Constraint Programming approach to integrate maximum workload constraints in preemptive jobshop scheduling
Terrien, Tanguy
Briand, Cyrille
Optimization and Control
Optimizing schedules in real-world settings often requires considering workload constraints, specially for human resources, to ensure regulatory compliance, impose rest periods, or level the workload over the working horizon. This paper focuses on tackling this family of constraints in the context of preemptive jobshop scheduling, as preemption is particularly relevant when human resources are involved (allowing personnel to flexibly switch between tasks). Preemption also offers theoretical insights as a relaxation of non-preemptive problems. The main contribution of this paper is a Constraint Programming approach designed to handle effectively maximum workload constraints in a preemptive setting, without decomposing activities into unit-duration tasks (which may be computationally prohibitive). Since workload constraints introduce significant additional complexity, we further propose a method that iteratively introduces the workload constraints into the problem, along with tailored heuristics specifically designed to guide the search efficiently. The experimental results demonstrate the effectiveness of our approach on a large set of instances, highlighting its performance compared to a well-known industrial solver, IBM's CP Optimizer.
title An iterative Constraint Programming approach to integrate maximum workload constraints in preemptive jobshop scheduling
topic Optimization and Control
url https://arxiv.org/abs/2605.20387