Research On The Supply Chain Network Integrated Location-inventory Problem With Uncertain Demand,Leadtime And Carbon Price

As a complex system,the supply chain network includes suppliers,distributors,retailers and other facilities.Many uncertain factors need to be considered in supply chain network design(e.g.,distribution center location,and allocation)and inventory control(e.g.,ordering,inventory level,and product flow decisions)to make the supply chain running efficiently.For the supply chain system,the decisions in different decision-making hierachies are interrelated with each other.To optimize the supply chain network at the strategic level or the inventory control at the tactical level alone can only lead to the suboptimal,which leads to the increasing of the total cost of the supply chain operation.Therefore,considering all kinds of uncertainties,researching on the integrated location-inventory problem will help supply chain enterprises to reduce supply chain costs and improve service efficiency.Through literature research and industry research,it is recognized that the most commonly considered uncertainties in supply chain management include demand uncertainty at the demand side and supply uncertainty at the supply side.In the face of severe environmental problems and the implementation of the second stage of national carbon-trading policy covering all industries after 2020,the supply chain and logistics industry will also face uncertainties in the carbon emission regulatory policy,such as the uncertainty of carbon-trading price in the carbon-trading policy.Many integrated location-inventory optimization researches are devoted to dealing with single uncertainty.The proposed models are simplified.The parameters,variables,constraints as well as the model settings are not as close to the complex reality as possible.The findings and management insights obtained are often invalid in the practice.Considering the shortcomings of the existing research,this paper takes the supply chain network location-inventory problem under uncertain demand as the research basis,and further includes the uncertainty of lead time and the uncertainty of carbon-trading price in carbon-trading policy,thus expanding to the study of supply chain network location-inventory problem under multiple uncertainties.For each problem,the paper builds the two-stage stochastic optimization model,and designs suitable algorithms to solve the models.Finally,the numerical experiments are conducted to give managial insights.This paper mainly investigates the following four location-inventory problems considering uncertainties:(1)In the research on the supply chain integrated location-inventory problem with the consideration of demand uncertainty,this paper adopts the reorder point inventory policy to build a demand scenario-based supply chain location-inventory two-stage stochastic model,which mainly investigates the supply chain network design and inventory decisions under different uncertain demand types(e.g.,stationary stochastic demand,non-stationary stochastic demand,and seasonal fluctuation non-stationary stochastic demand).The objective function of the two-stage stochastic optimization model maximizes the expected profit of supply chain.The costs include the fixed distribution center opening cost,the supply channel construction cost,product transportation cost,product procurement cost,inventory storage cost,ordering cost,and back-ordering cost.Through Monte Carlo simulation and sample average approximation(SAA),the confidence upper and lower bounds are obtained,as well as near optimal solutions of the two-stage stochastic optimization model.The numerical experiments include the effectiveness analysis of SAA method to solve the two-stage stochastic optimization model,the comparison of supply chain location-inventory decisions under three uncertain demand types,and the analysis of supply chain location-allocation decisions under different budget constraints.(2)In the research on the supply chain integrated location-inventory problem with the consideration of demand and leadtime uncertainties,this paper uses the periodic review,order-up-to level(T,S)inventory policy to build a demand and leadtime scenario-based supply chain location-inventory two-stage stochastic model,which mainly studies the optimal location-inventory decisions under variety of uncertain demand types(e.g.,stationary stochastic demand and non-stationary stochastic demand)and different degrees of uncertainty lead time(e.g.,determinisitic leadtime,low uncertainty leadtime,and high uncertainty leadtime).A scenario based Benders Decomposition algorithm is designed.In iterations,feasible cuts and scenario-based optimal cuts are added to the relaxed Benders master problem,thus converging to the global optimal.Numerical experiments include the effectiveness analysis of the Benders Decomposition Algorithm,the sensitivity analysis of supply chain location-inventory decisions under uncertain demand and uncertain leadtime.(3)In the study of the supply chain integrated location-inventory problem with the consideration of demand and carbon price uncertainties,this paper uses the periodic review,reorder point order-up-to level(T,s,S)inventory policy to build a demand and carbon price scenario-based supply chain location-inventory two-stage stochastic model under the carbon-trading regulation.The objective function of the two-stage stochastic optimization model further includes the carbon emission quota revenue,the distribution center implementation carbon emission,and the transportation carbon emission.In this paper,two sequential-solving modes are proposed,namely the location-oriented sequential and the demand-oriented sequential,to solve the strategic and tactical subproblems decomposed from the original stochastic optimization model in a certain order,and an integrated heuristic algorithm based on the simulated annealing is designed.Numerical experiments include the effectiveness analysis of the heuristic algorithm,the analysis of the two sequential-solving modes in decision-making and the advantage of the integrated heuristic algorithm over the two sequential-solving approaches,and the sensitivity analysis of supply chain location-inventory decision to the carbon quota and different cost structures.(4)In the study of supply chain carbon-emission compliance location inventory problem with demand,leadtime,and carbon price uncertainties,this paper also adopts the periodic review,reorder point order-up-to level(T,s,S)inventory policy to build demand,leadtime,and carbon price scenario-based supply chain location-inventory two-stage stochastic model under a multi-year carbon-trading scheme.The model further increases the carbon trading decisions,carbon trading revenue/cost in the objective,carbon emission-compliance constraints,and the inventory storage carbon emission.Due to the consideration of the inventory storage carbon emissions,the optimal parameter settings of the inventory policy in this chapter weigh the inventory storage cost,backordering cost,and the inventory storage carbon emission.A three-phase hierarchical matheuristic algorithm is proposed to solve the two-stage stochastic model,which includes the location-allocation neighborhood exploration strategies,the inventory control and carbon-trading heuristics,and the intensification phase to move the near optimal to the global optimal.The numerical experiments include the effectiveness of three-phase hierarchical heuristic algorithm,the optimal supply chain decisions and the carbon emissions under different carbon emission policies(e.g.,carbon tax,carbon quota,carbon quota carbon tax and carbon trading),the impact of carbon price level and volatility on supply chain location-inventory decisions and carbon emissions under the carbon-trading regulation,and sensitivity analysis of the supply chain decisions under various uncertaities.