Flexible job scheduling under consideration of time and energy consumption using enhanced iterative deferred acceptance algorithm

Articles in Press

Document Type : Research Paper

Author

University of Tehran, College of Engineering, Faculty of Industrial Engineering

10.22059/aie.2024.378291.1898

Abstract

This paper highlights the shift in the industrial sector towards a decentralized structure, focusing the importance of energy efficiency for manufacturers and the need for quick job completion to satisfy customers. The study proposes a matching game approach using the Job Scheduling Problem (JSP) to address both manufacturer and customer concerns. It introduces the Deferred Acceptance (DA) algorithm, as a notable matching algorithm, to create stable and optimal matches between machines and operations, incorporating the W-value concept to represent willingness values between partners. The Enhanced Iterative DA (EIDA) algorithm, enhanced with the W-value, shows improved job completion time, reduced energy consumption, and faster runtime compared to the Genetic Algorithm (GA). Through experiments, our enhanced iterative DA (EIDA) algorithm results in an average 6.40% increase in job completion time and a 16.60% reduction in manufacturers' energy consumption compared to the Genetic Algorithm (GA). Moreover, utilizing the W-value leads to a 19.03% average runtime improvement.

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Advances in Industrial Engineering

Articles in Press, Accepted Manuscript
Available Online from 07 July 2024

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