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【Mingli Lecture, 2023, Issue 19】4-14 Professor Raymond Chong, University of Newcastle:

Time: April 14th (Friday) 15:30-17:30 PM

Location: 217, Zhongguancun Main Building

Reported by: Professor Raymond Chong, University of Newcastle

Reported by:

Professor Raymond Chong is a tenured academic staff member with the University of Newcastle, Australia His research areas include agent based modeling, machine learning, and optimization Raymond is the Editor in Chief of the Journal of Systems and Information Technology, and an Editor for the Journal Engineering Applications of Artistic Intelligence He has also preserved in a Guest Editor role for a number of reproducible international journals, such as the International Journal of Production Economics and European Journal of Operational Research To date, Raymond has published more than 250 papers His publications have been cited over 6000 times, and his h-index is closed to 40

Introduction to report content:This talk will discuss about the research on the use of machine on/off control for energy-efficient productions scheduling, which is an important extension of energy-efficient production scheduling research. The inspiration of this extension is that a machine must be turned off if it needs to be maintained, and an already-turned-off machine can be maintained without needing to be restarted. We therefore formulate an energy-efficient production scheduling problem with machine maintenance through machine on/off control, aiming to optimise three objectives – the makespan, total number of machine restarts, and energy consumption – at the same time. Four rules are designed to set the machine on/off criteria, maintenance periods and predefined maintenance window. Three effective heuristics are proposed to insert the maintenance activities into the solutions and move their maintenance-operation blocks to optimise the objectives.Our proposed heuristics, unlike traditionalheuristic algorithms, are expected to be applicable and effective even if we change the objectives and constraints, require minimal computational time (only a few seconds) to optimise a scheduling solution, and can solve different types of scheduling problems without needing any modification.

(Undertaken by: Department of Management Engineering, Research and Academic Exchange Center)

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