A Hybrid Genetic Algorithm for Minimizing Energy Consumption in Flow Shops Considering Ultra-low Idle State

摘要

Nowadays, there has been an increasing concern on the energy consumption in the manufacturing industry. As the basic energy-consuming equipment of workshops, numerical control (NC) machine tools consume huge amount of energy, a large part of which is wasted by idle state. In this paper, a kind of ultra-low idle state of machine tools was proposed by turning off some auxiliary parts in idle state to save energy. In view of the characteristic that it takes a certain time to restore the ultra-low idle state to the processing state, a hybrid algorithm combined with genetic algorithm (GA) for job scheduling was developed by adjusting the state of various NC machine tools. A case study for flow shop scheduling with ultra-low idle state was conducted to verify the proposed method, which performed well in energy-saving.