Energy-awareness scheduling of unrelated parallel machine problems with multiple resource constraints

Abstract

The environmental and economic pressures caused by energy consumption arouse energy-saving consciousness of the manufacturing industry. To this end, the paper integrates energy-awareness into the research of the unrelated parallel machines scheduling problem with multiple auxiliary resources which is typical in the photolithography process of wafer fabrication. With a comprehensive consideration of jobs requiring different processing demands, setup times, different ready times, resource constraints and energy consumption, a scheduling model with a multi-objective function of minimising the total weighted completion time and total energy consumption of the system is developed. On the basis of the model, a modified multi-objective artificial immune algorithm integrated with non-domination sorting strategy is put forward to crack the problem. Furthermore, in order to improve the performance of the proposed algorithm, clone operators, neighbourhood search operators, elite-preservation operators are applied to the algorithm. Finally, the experimental results and analysis validate that the presented algorithm is efficient and effective.