关键词: 种群增量学习算法, 生产调度, 碳排放, 最大完成时间

Abstract: To introduce carbon emission into production scheduling optimization,aiming at the production scheduling problem with limited waiting time,a dual-objective optimization model for minimizing makespan and carbon emissions was constructed,and it was rebuilt as a single-objective model by using weighting utility function and standardized method.In addition,an Improved population-based increased learning (IPBIL) was utilized to solve the problem.Extensive simulation was conducted and the results showed that the operation waiting time had little impact on carbon emissions and lots of carbon were generated with equipment idling,thus the carbon emission could be reduced effectively by improving the utilization rate of the equipment.Moreover,makespan was inversely related to the carbon emission that enterprises needed to pay a greater cost of carbon emissions to quick respond to customer requirements,but they should relax economic indicators to reduce the cost of carbon emissions in carbon rights trading.

Key words: population-based increased learning algorithm, production scheduling, carbon emissions, makespan