A Green Flexible Job-Shop Scheduling Model for Multiple AGVs Considering Carbon Footprint

Abstract

Green and low carbon automated production has become a research hotspot. In this paper, the AGV transport resource constraint, machine layout and job setup time have been integrated into the background of a flexible job shop. From a whole life-cycle perspective, the AGV allocation strategy has been formulated by simulating multiple scenarios within the production system. Aimed at makespan, carbon footprint, and machine load, a green low-carbon flexible job shop scheduling model with multiple transport equipment (GFJSP-MT) has been constructed. To address this problem, a relevant case dataset was formed, and a heuristic strategy NSGA-II using a real number encoded embedded cycle to replace repeated individuals was proposed. Through longitudinal and horizontal comparisons, the effectiveness of the AGV allocation strategy has been verified and the optimum number of AGVs in the case determined. Finally the quality and diversity of the Pareto frontier solutions are compared and the scheduling scheme for each sub-objective are discussed. The results show that the model and algorithm constructed in this paper can effectively achieve the optimal scheduling of green flexible shop production.