Idle time and capacity control for a single machine scheduling problem with dynamic electricity pricing

Seokgi Lee, Mona Issabakhsh, Hyun Woo Jeon, Seong Wook Hwang and Byung Chung ()
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Seokgi Lee: University of Miami
Mona Issabakhsh: University of Miami
Hyun Woo Jeon: Louisiana State University
Seong Wook Hwang: Hongik University
Byung Chung: Yonsei University

Operations Management Research, 2020, vol. 13, issue 3, No 5, 197-217

Abstract: Abstract In this paper, we develop a dynamic control algorithm for production scheduling that considers machine capacity and idle time controls and aims at satisfying time related production demand and reducing energy consumption in a unified manner. A mixed integer nonlinear programming (MINLP) model is developed to determine job arrival sequence for a machine and machine capacity while minimizing resulting costs of just-in-time production, machine repair, and energy consumption during machine idle time and nominal processing. A dynamic control algorithm based on feedback control of continuous variables is also developed to determine an energy-efficient production schedule with proper machine capacity and turn-off schedules. Energy, JIT, and maintenance costs of the proposed approach are examined using real energy and machining parameters of a HAAS VF0 milling machine. Algorithmic performance of the proposed dynamic control approach is compared to other heuristics, adaptive large neighborhood search (ALNS), and genetic algorithm (GA) with a speed optimization (SO) component. Experimental results show that the proposed algorithm improved performance by an average 10.0 ~ 93.8% and 0.52 ~ 22.9% compared to GA and ALNS with the SO module, respectively.

Keywords: Production scheduling; Machinery capacity control; Machine idle time; Just-in-time production; Energy consumption; Machine on-off schedule (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s12063-020-00156-x

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