Research On Multi-objective Optimization Model For Location-Distribution In Low Carbon Supply Chain Under Demand Uncertainty

Global climate warming is a major problem and challenge for humanity in the 21st century, and the CO2 produced by anthropogenic activities is the main reason for intensifing the greenhouse effect. Logistics and supply chain operations are the most important part of economic activities today, and they are the main source of air pollution and greenhouse gas emissions. Thus this paper selects location-distribution problems in supply chain as the research object, using multi-objective optimization method to model low carbon supply chain location-distribution problems, and analyzes the impact of carbon emissions on decision-making by trading-off between cost and carbon emissions. In addition, this paper takes the practical factor of demand uncertainty into account, exploring the impact of demand uncertainty on supply chain location-distribution decisions, which has important theoretical and practical significance.The main work of this paper includes the following:(1) The location-distribution multi-objective optimization model of low-carbon supply chain is established. First, the paper calculates carbon emissions generated in the process of supply chain location-distribution, obtaining the carbon emissions in all aspects of the location-distribution process. On this basis, the paper establishes a location-distribution multi-objective model in low-carbon supply chain by multi-objective optimization methods, exploring the impact of carbon emission factor on the cost and decisions about location-distribution through weighing the relationship between carbon emissions target and the cost target, and obtain optimal location-distribution decisions to make both the cost and carbon emissions targets optimal.(2)The multi-objective optimization model for low carbon supply chain location-distribution under demand uncertainty is built. And this paper takes both carbon emissions factor and demand uncertainty factor into account. By constructing different scenarios for deal with demand uncertainty, the paper solves the model and analyzes the results and draws a conclusion that the uncertain demand requirements location-distribution system to allocate more resources to cope with fluctuations in demand, and the greater the demand uncertainty, the more resources needed to allocate.(3) Model solution basing on multi-objective differential evolution algorithm and analysis of numerical examples. The paper uses Northeast China Petroleum Chemical Sales Company distribution network datas to build examples, and uses an improved multi-objective differential evolution algorithm to solve the model, which verifies the validity of the model. On this basis, the paper analyzes the effect of both carbon emissions and demand uncertainty on the decisions about supply chain location-distribution, and gets a serious of useful conclusions, which provides a certain reference for the actual operation of enterprises.The multi-objective optimization model in the paper for low carbon supply chain location-distribution under demand uncertainty is a meaningful abundance and supplement for low-carbon supply chains location-distribution theory, and it has an important theoretical and practical significance and the results and conclusions obtained in the paper provide some theoretical guidance and reference value for the practical operation of enterprises.