Low Carbon Multi-Objective Shop Scheduling Based On Genetic and Variable Neighborhood Algorithm

Abstract

Abstract Aiming at the low-carbon scheduling problem of flexible job shop, the carbon emission and key scheduling objectives of machining system are studied. Firstly, the carbon emissions directly generated by machines and indirectly generated by waste treatment are considered in the calculation of carbon emissions, and then a multi-objective optimization model is established with completion time, total machine load and carbon emissions as the objective function; secondly, the hybrid algorithm of genetic variable neighborhood is designed to solve the optimization model, and the completion time, total machine load. Finally, the production example is simulated in Matlab environment. The experimental results show that the multi-objective scheduling model is feasible and effective. According to the production situation of the workshop, the producer can allocate the weight of each objective, and reduce the carbon emissions in the production process on the premise of ensuring the balance of the completion time and equipment utilization.