4.7 Article

Energy saving scheduling strategy for job shop under TOU and tiered electricity price

Journal

ALEXANDRIA ENGINEERING JOURNAL
Volume 61, Issue 1, Pages 459-467

Publisher

ELSEVIER
DOI: 10.1016/j.aej.2021.06.008

Keywords

Energy saving scheduling; TOU and tiered electricity price; Firefly algorithm

Funding

  1. Doctoral innovation fund of Xi'an University of Technology
  2. National Natural Science Foundation of China [52005404]
  3. China Postdoctoral Science Foundation [2020M673612XB]

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This study addresses the energy-saving scheduling issue in job shops of order-oriented manufacturing enterprises, proposing an improved Firefly Algorithm to tackle the discontinuous domain problem. By redesigning the coding structure and updating operations, the algorithm shows effectiveness in reducing energy consumption costs.
In view of the energy-saving scheduling problem of job shop in the order-oriented manufacturing enterprise, it is necessary to consider the energy consumption of equipment processing and standby. Considering the Time-of-Use (TOU) and tiered electricity price, a mathematical model is established by introducing the switch strategy in the idle time of equipment to reduce the cost of power consumption in production and assembly. In order to solve the discontinuous domain problem that the standard Firefly Algorithm (FA) is not suitable for workshop energy saving scheduling, an improved FA is used to solve the mathematical model. The coding, decoding and location updating of the algorithm are redesigned. A three-layer coding structure based on the workpiece sequence, starting time and switch strategy is designed; for the iterative process of work piece sequence encoding, the Hamming distance is used to replace the Euclidean distance to calculate the position distance between the firefly individuals. Precedence preservation order-based crossover (POX) crossover is used to replace the position updating operation to ensure the feasibility of the solution. Finally, the correctness of the mathematical model and the effectiveness of the algorithm are verified by examples. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.

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