Study On Supply Chain Optimization Model Under Low-Carbon Policy And Uncertainty Environment

With global economic and social development being increasingly improved,as the important companion---environmental problems have become more and more prominent,and threatened human beings' health,survival and development.Being regarded as one of the top-ten serious environmental problems,global warming is forcing the countries of the world to formulate the corresponding low-carbon regulation policies according to their own national conditions.The supply chain enterprises being important subjects of social activities not only need to achieve the entire supply chain's overall goal of profits maximization or costs minimization,but also need to assume the responsibility to protect the environment under the low-carbon regulation policy,to achieve the ultimate goal of reducing carbon emissions,so as to contribute to the low-carbon economy.Meanwhile,the implementation of low-carbon policy makes supply chain optimization more complex than conventional supply chain optimization,because the decision goal changes,besides,some decision variables such as carbon emissions,carbon trading decision variables are added to the traditional decision variables,and also decision environment changes,limitation of carbon constraints as well as production capacity and funds constraints need to be considered.On the other hand,in the actual situation,due to the changes of economic and environmental factors,such as the production of new products,the use of new equipments,and the selection of new routes,some parameters of supply chain can not through the historical data to obtain accurately,which causes uncertainty of supply chain and great distress for supply chain optimization.In order to solve the problem of supply chain optimization modeling under low-carbon policy and uncertainty environment,especially when supply chain is under these three low-carbon regulation policies---Carbon emissions tax,Mandatory carbon emissions capacity(Cap)and Cap-and-trade,and when uncertainty factors of the supply chain are fuzzy,this paper put forward supply chain optimization models under these three low-carbon policys based on fuzzy programming theory,then based on fuzzy theory and genetic algorithm,this paper designed three kinds of algorithms to solve the proposed fuzzy models.This thesis could provide a new idea for supply chain operations management under low-carbon regulation policy and uncertainty environment,and also could provide a referential basis for the government making the carbon policy.The main research contents are listed as follows:(1)Based on the analysis of the importance of environmental problems and the uncertainty in the supply chain operation,this paper designs a framework of supply chain optimization under the influences of low carbon regulation and uncertain environment,then analyzes the global warming and other environmental problems,in addition to the trend of social and economic development,summarizes three kinds of low carbon policy which are implemented by many countries: Carbon tax regulation,Cap regulation,and Cap-and-trade regulation,also analyzes the effect of these low carbon policy on national and industry,as well as the supply chain management,at the same time,also sums up the main uncertainty factors related to the process of supply chain operation,and puts forward the research content of this paper on the basis of the above work.(2)Under the regulation of carbon tax policy,an optimization model of four-echelon supply chain with fuzzy costs is established,in which there are four party enterprises---suppliers,manufacturers,distributers and retailers.In centralized decision mode,for the existence of different uncertainties in each node of supply chain,considering uncertain factors of suppliers' supply capacity,manufacturers' production capacity,and the transport capacity of manufacturers and distributors as triangular fuzzy numbers,this paper develops an optimization model of supply chain with fuzzy cost under carbon tax policy,whose objective function is to minimize the total cost of procurement costs,production cost,transportation cost and the cost of carbon emission.Based on fuzzy possibility theory and necessity theory,this paper applies an interactive fractile approach proposed by Inuiguchi to transfer the fuzzy programming models and solve them,and finally discusses the impacts of carbon tax rate variation for the decision,carbon dioxide emissions,carbon costs,the total cost,and the percentage of carbon costs in the total cost,respectively.(3)Under the Cap regulation policy,an optimization model of two-echelon supply chain with fuzzy demand is established.The main purpose of this problem focuses on modeling the optimization problem of a two-echelon supply chain consisting of suppliers and sellers by using fuzzy mathematical nonlinear programming approach.In order to research conveniently,this model just considers the demand of retailers to be fuzzy,allows being out of stock and returning products which do not affect being selled again and can be used as the new products through processing and packaging simply,and applies trapezoidal fuzzy variable to describe the demand.Its objective function is to minimize the total cost of the procurement cost,the storage cost,the delivering cost,the keeping cost,the shortage cost and the handling cost of returns.Based on fuzzy credibility theory,this paper presents three fuzzy mathematical programming models---fuzzy expected value model,fuzzy chance-constrained programming model,and the dependent-chance constrained programming model,then designs a hybrid intelligent algorithm integrating fuzzy simulation and genetic algorithm to solve the proposed fuzzy programming models and gives the steps of solving models.Finally,a numerical example is provided to verify the efficiency of the designed algorithm.(4)Under the regulation of Cap-and-trade policy,an optimization model of two-echelon supply chain with fuzzy demand is established,in which there are suppliers and retailers.In order to calculate simplely,when this paper analyzes systemly this two-echelon supply chain,also only considers the demand of retailers to be fuzzy,but allows being out of stock and returning products which do not affect being selled again and can be used as the new products through processing and packaging simply.Then this paper also uses trapezoidal fuzzy variable to describe the demand and develops an optimization model of supply chain with fuzzy demand under Cap-and-trade policy,whose objective function is also to minimize the total cost of the procurement cost,the storage cost,the delivering cost,the keeping cost,the shortage cost and the handling cost of returns.Based on the fuzzy mathematical nonlinear programming approach,this paper presents three fuzzy mathematical programming models---fuzzy expected value model,fuzzy chance-constrained programming model,and the dependent-chance constrained programming model,then introduces credibility theory to transform the proposed fuzzy models into crisp models,and gives three equivalence theorems.Finally,an illustrative example is presented to demonstrate the effectiveness of the proposed models.