Efficient Algorithms for Energy-Aware Single-Machine Scheduling with Battery Storage
Abstract
Energy-aware scheduling has become a central challenge in modern manufacturing environments. As industries increasingly aim to reduce operational costs and carbon emissions, aligning production activities with electricity tariffs is increasingly important. The integration of battery energy storage system (BESS) further enhances the potential to reduce energy purchase costs; however, incorporating such systems introduces complex interdependencies between job scheduling and BESS management decisions, significantly complicating the problem structure.\\In this work, we study the problem of minimizing the energy cost of executing a set of jobs on a single machine within a fixed time horizon, where electricity prices follow a Time-of-Use (TOU) tariff. In addition, we consider the presence of a BESS that can be charged from the grid and discharged during high-price periods to reduce overall energy costs. To efficiently address this problem, we propose and analyze two matheuristic algorithm variants designed to effectively coordinate production scheduling and BESS usage decisions.
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BibTeX
@misc{forte2026efficient,
title = {{Efficient Algorithms for Energy-Aware Single-Machine Scheduling with Battery Storage}},
author = {Luca Forte and Stijn De Vuyst and Pieter Leyman},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.11455},
eprint = {2609.11455},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.11455},
note = {CC BY-NC-SA 4.0},
}
RIS
TY - UNPB
TI - Efficient Algorithms for Energy-Aware Single-Machine Scheduling with Battery Storage
AU - Luca Forte
AU - Stijn De Vuyst
AU - Pieter Leyman
PY - 2026
DA - 2026/09/10
PB - arXiv
DO - 10.48550/arxiv.2609.11455
UR - https://arxiv.org/abs/2609.11455
AB - Energy-aware scheduling has become a central challenge in modern manufacturing environments. As industries increasingly aim to reduce operational costs and carbon emissions, aligning production activities with electricity tariffs is increasingly important. The integration of battery energy storage system (BESS) further enhances the potential to reduce energy purchase costs; however, incorporating such systems introduces complex interdependencies between job scheduling and BESS management decisions, significantly complicating the problem structure.\\In this work, we study the problem of minimizing the energy cost of executing a set of jobs on a single machine within a fixed time horizon, where electricity prices follow a Time-of-Use (TOU) tariff. In addition, we consider the presence of a BESS that can be charged from the grid and discharged during high-price periods to reduce overall energy costs. To efficiently address this problem, we propose and analyze two matheuristic algorithm variants designed to effectively coordinate production scheduling and BESS usage decisions.
ER -