Multi-objective optimisation for energy-aware flexible job-shop scheduling problem with assembly operations

There is a lack of studies on joint optimisation of flexible job-shop scheduling problem (FJSP) considering energy consumption and production efficiency in the machining-assembly system. Thus, in this paper, we propose a methodology for multi-objective optimisation of energy-aware flexible job-shop scheduling during machining and assembly operations. First, a mixed integrated mathematical model is developed to improve production efficiency and minimise energy consumption. Then, a novel heuristic algorithm integrated particle swarm optimisation (PSO) and genetic algorithm (GA) is developed to address the established multi-objective problem. Moreover, numerical examples are carried out to verify the validity and performance of the solving methods in achieving energy awareness in the manufacturing system. Computational results are presented to demonstrate the advantage of solving the problem compared with the exact method and common heuristic algorithms, and the trade-off between production efficiency and energy efficiency is analysed to make the final decision for managers.

Automated summary

This paper proposes a methodology for multi-objective optimisation of energy-aware flexible job-shop scheduling by developing a mixed integrated mathematical model and heuristic algorithm. Numerical examples demonstrate the effectiveness and performance of the method in achieving energy awareness in manufacturing systems.