The Study On Sustainable Supply Chain Planning By Equilibrium Optimization Method

Sustainable supply chain planning combines sustainable development with sup-ply chain decision-making for improving and balancing economic,environmental and social performance.Supply chain planning is an important function of sustainable supply chain management and plays a key guiding role in the operation of supply chain.The uncertainty in supply chain operation is one of the main obstacles to work out a feasible and effective supply chain planning.In many cases,both sta-tistical distribution and experts' judgment are important references for forecasting parameters' changes.The uncertainty in supply chain planning may include both randomness and fuzziness.Therefore,a new optimization method,which can deal with both randomness and fuzziness,is required to model sustainable supply chain planning problem in hybrid uncertain environments.This thesis proposes a new op-timization method for hybrid uncertain sustainable supply chain planning problems,which can provide a reference for decision makers to make supply chain planning in line with the needs of economic and social developmentIn this thesis,two kinds of new equilibrium two-stage optimization methods are proposed to the sustainable supply chain planning problem with recourse decisions These two optimization methods are the combination of stochastic and credibilistic optimization methods,which can not only deal with the twofold uncertainty,but also make recourse decisions as early as possible.From the perspective of core en-terprises,based on the new equilibrium two-stage optimization methods and risk aversion criteria,multi-objective supplier selection and demand allocation planning model and supply chain production and transportation planning model are estab-lished,respectively.According to the structural characteristics of the proposed mod-els,either the equivalent stochastic programming or the credibilistic programming is deduced.From the same perspective,a single-stage equilibrium expected value model is established to decide the location and distribution planning of distribution centers for the supply chain,and a single-stage equilibrium chance maximization model is established to solve the closed-loop supply chain planning problem of pro-ducing new product and reusing the used product.Their equivalent mixed integer nonlinear programming models are deduced.The effectiveness of four supply chain planning models is illustrated by numerical experiments.The main innovations of this thesis include the following several aspects:(?)Integrating stochastic and credibilistic optimization methods into an optimization framework in an equilibrium mode,effectively,two kinds of equilibrium two-stage optimization methods are proposed.(?)To measure the risks resulted from the subjective uncertainty,the concept of conditional value at risk of fuzzy variables is proposed.(?)For sustainable supply chain planning problems,static equilibrium optimization methods are established to determine the optimal locations of distribu-tion centers,distribution planning,the production planning of new product and the reusing planning of used product,and dynamic equilibrium two-stage optimization methods are established to determine the optimal supplier,ordering planning,pro-duction and transportation planning.(?)Under some important distributions,the equilibrium models are transformed into equivalent or approximate mathematical programmming models.Then,according to the characteristics of the mathematical programmming models,this thesis designs an appropriate heuristic algorithm or ap-plies commercial software to solve them.(?)Some numerical examples of sustainable supply chain planning problems are applied for comparative studies to illustrate the effectiveness and practicability of the proposed equilibrium optimization methods.