Flexible Flow Shop Scheduling and Energy Saving Optimization Strategy under Low Carbon Target

Abstract

In order to reduce the carbon emissions of the flow shop which consists of unrelated parallel machine, a kind of scheduling mathematical mode with low carbon emission target is built by analyzing the carbon emissions of the machine tools under different running conditions. Not only the carbon emissions produced in the handling process which is rarely discussed in the previous studies, but also the carbon emissions produced during the start-up and shutdown process of the selected machine tools are considered in the model. Based on this model, a multi-state alternation energy saving optimization strategy is proposed to reduce carbon emissions during the idle waiting period of machine tools. An improved genetic algorithm is employed to solve this optimization problem. In the end, the t cases are studied to validate the strategy.