The impact of incentive-based programmes on job-shop scheduling with variable machine speeds

Abstract

Given the high demand for energy in the manufacturing industry and the increasing use of renewable but volatile energy sources, it becomes increasingly important to coordinate production and energy availability. With the help of incentive-based programmes, grid operators can incentivise consumers to adjust power demand in critical situations such that grid stability is not threatened. On the consumer side, energy-efficient scheduling models can be used to make energy consumption more flexible. This paper proposes a bi-objective job-shop scheduling problem with variable machine speeds that aims on minimising the total energy consumption and total weighted tardiness simultaneously. We use a genetic algorithm to solve the model and derive Pareto frontiers to analyse the trade-off between both conflicting objectives. We gain insights into how incentive-based programmes can be integrated into machine scheduling models and analyse the potential interdependencies and benefits that result from this integration.

KEYWORDS:

• Job-shop scheduling
• energy-efficient production planning
• genetic algorithm
• sustainable manufacturing
• demand response programmes
• incentive-based programmes

Acknowledgements

This paper is a revised and extended version of the conference paper ‘Energy-efficient job shop scheduling considering processing speed and incentive-based programmes’ that was presented at 10th IFAC Conference on Manufacturing Modelling, Management and Control in Nantes, France, 2022. The authors are grateful to the anonymous reviewers for their constructive comments on an earlier version of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by the State of Hesse for energy subsidies within the scope of the Hessian Energy Act (Hessischen Energiegesetztes, HEG) of 9 October 2019 with funds from the State of Hesse and with the kind support of the House of Energy [grant number E/411/71632164].

Notes on contributors

Marc Füchtenhans

Marc Füchtenhans received B.Sc. and M.Sc. degrees in business mathematics from Technical University of Darmstadt in 2014 and 2018. Since 2018, he is a Research Associate and Ph.D. student at the Institute of Production and Supply Chain Management at Technical University of Darmstadt. His research interests include sustainable solutions in the context of production and supply chain management. His works have appeared in the International Journal of Production Research and the International Journal of Logistics Research and Applications, among others.

Christoph H. Glock

Christoph H. Glock is a full professor and head of the Institute of Production and Supply Chain Management at Technical University of Darmstadt. His research interests include inventory management, supply chain management, warehousing, sustainable production and human factors in logistics and inventory systems. He has published in renowned international journals, such as the European Journal of Operational Research, Decision Sciences, the International Journal of Production Economics, the International Journal of Production Research, Omega, Transportation Research Part E or IISE Transactions.