Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times

<div><p>This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration of the completion time and the total energy consumption under stochastic processing times. The case study on GM Corporation verifies that the NSGA-II used in this paper is effective and has advantages to solve the proposed model comparing with HPSO and PSO+SA. The idea and method of the paper can be generalized widely in the manufacturing industry, because it can reduce the energy consumption of the energy-intensive manufacturing enterprise with less investment when the new approach is applied in existing systems.</p></div

The influence of uncertain parameters on the total energy consumption.

<p>The influence of uncertain parameters on the total energy consumption.</p

The graphical research framework of this paper.

<p>The graphical research framework of this paper.</p

The process of NSGA-II.

<p>The process of NSGA-II.</p

The influence of uncertain parameters on the completion time.

<p>The influence of uncertain parameters on the completion time.</p

Comparison of case results.

<p>Comparison of case results.</p