Energy-aware optimization for the two-agent scheduling problem with fuzzy processing times

• Published in: International journal on interactive design and manufacturing Vol. 17; no. 1; pp. 237 - 248
• Main Authors: Liu, Guo-Sheng, Tu, Mei, Tang, Ying-Si, Ding, Tian-Xiang
• Format: Journal Article
• Language: English
• Published: Paris Springer Paris 01.02.2023; Springer Nature B.V
• Subjects: Batch processing; CAE) and Design; Computer-Aided Engineering (CAD; Electronics and Microelectronics; Energy conservation; Energy consumption; Energy management; Engineering; Engineering Design; Genetic algorithms; Heuristic; Industrial Design; Instrumentation; Linear programming; Manufacturing; Mathematical programming; Mechanical Engineering; Multiple objective analysis; Numerical analysis; Objectives; Optimization; Original Paper; Particle swarm optimization; Reduction; Scheduling; Sorting algorithms; Velocity; Agent based systems; Energy management; Optimization; Fuzzy methods; Genetic algorithms
• ISSN: 1955-2513; 1955-2505
• DOI: 10.1007/s12008-022-00927-9

Due to the energy shortage and global warming, modern manufacturing enterprises have had to face the competition from complex and ever-changing markets and the challenge of energy saving and pollution reduction. This paper studies a typical two-agent scheduling problem with energy-aware consideration, which includes a type of online agent that requires completion of its jobs as early as possible and the other type of offline agent that requires periodic completion of its jobs. We have proposed a Multi-Objective Hybrid Genetic Algorithm (MOHGA) to solve this two-agent scheduling problem where the agents’ completion times and the manufacturer’s energy consumption are the optimized objectives. The proposed MOHGA introduces the Particle Swarm Optimization (PSO) process to avoid immature convergence trap. Results from numerical experiments show this algorithm is superior to the Non-dominated Sorting Genetic Algorithm II and multi-objective PSO. With the help of MOHGA, the energy-saving schemes ‘turn-off’ and ‘velocity control’ can achieve at least 2.2% and 4.7% energy consumption reduction respectively in two-agent scheduling problem. Further numerical analysis shows that for some special cases a much greater energy-saving potential (approximately 49.1%) can be explored if proper postpone (8.4%) of the completion of the jobs is acceptable.