Integrated Optimization Of Inventory,price And Quality For Perishable Products

Perishable products are characterized by the perishability of quality and inventory levels,which have significant negative impacts on the management.In order to effectively manage it,this thesis studies the following four problems,which are the integrated ordering and pricing policies for the inventory system of perishable products,the integrated ordering,pricing and freshness-keeping policies for the inventory system of perishable products,the game-based ordering,pricing and freshness-keeping policies between the supplier and the retailer,and the vehicle routing for the supply chain logistics of perishable products considering freshness-keeping effort.（1）The integrated ordering,pricing policies for the inventory system of perishable productsThe optimal policy is proposed for the inventory system of perishable products to maximize the profit,where the deterioration process is stochastic and the inventory level is inaccurate.First,a discrete linear stochastic dynamics system is proposed,in which define the inventory levels of the freshest and fresh perishable products be the system state.The random variables are used to represent the process error and the measurement error,which follow the normal distribution.For the deterministic system,the optimal ordering and pricing policies are obtained using the policy iteration algorithm.Then,to overcome the negative impacts of the above two errors,the Kalman state estimate-based iteration algorithm is proposed to obtain the optimal estimate state,which can provide more accurate input for the integrated policy.Finally,the results of the numerical simulations illustrate that the Kalman state estimate can reduce the variance between the real inventory level and the optimal estimated value to improve the accuracy of measuring the system state.On the other hand,the Kalman state estimate can reduce the probability of shortage and increase profit.（2）The integrated ordering,pricing and freshness-keeping policies for the inventory system of perishable productsThe integrated ordering,pricing,and freshness-keeping policies are proposed for the inventory systems for perishable products to maximize the profit,where the freshenss-keeping effort can reduce the deterioration rate to improve the available inventory level.In the case of the single period for the deterministic system,a series of nonlinear programming in the different cases are proposed,and the optimal single-period ordering,pricing,and freshness-keeping policies（i.e.,the myopic strategies）are derived analytically by using the Karush-Kuhn-Tucker（KKT）condition.We find that in some scenarios where products deteriorate with a high rate,the freshness-keeping effort depends on the inventory level and has a piecewise structure.When the inventory level is not too high or too low,it is appropriate to employ freshness-keeping effort;otherwise,it is not.In addition,the order policy has（s,S）-type structure.Based on the solution of the single-period case,the stochastic problem in the infinite horizon is investigated,where the randomness in demand and deterioration processes are considered.A value iteration-based approximate dynamic programming algorithm is proposed to obtain the joint near-optimal policy,in which the value function is approximated by using the locally weighted linear regression algorithm.In the algorithm,the policy structure in the deterministic case is used to reduce the search range of decision space.Finally,numerical simulations and sensitive analysis on some key system parameters illustrate that the freshness-keeping effort has positive effect to improve profit.Compared with the quadratic function,the proposed algorithm is robust to the uncertainty of the demand and the deterioration process.（3）The game-based ordering,pricing and freshness-keeping policies between the supplier and the retailerThe game-based policy is proposed to maximize the profits for the retailer and the supplier.In such a system,the demand rate depends on the product quality and retail price,as well as some unknown random factors.To study this problem,we adopt the three practical sense parameters（i.e.,the inherent deterioration rate,the respond constant,the decay constant）to develop the dynamics of deterioration process of the freshness-keeping effort.Compared with static models,the proposed dynamics can depict the dynamic characteristics（cumulative effect and saturation property）.Based on that,the relationship between the retailer and the supplier is modeled as a Stackelberg game,in which the supplier is the leader and the retailer is the follower.Based on the optimal principle of dynamic programming,the optimal equilibrium policy of the Stackelberg game is obtained,including the retailer’s price,fresh-keeping effort,order quantity,and supplier’s wholesale price and optimal freshness-keeping subsidy rate,then analyze the closed policy using the approximate dynamic programming.Moreover,the condition that the equilibrium policy is to be optimal is also analyzed.Finally,numerical simulations and sensitivity analyses on some key parameters are conducted to illustrate the effect of the proposed policy and provide some management insights for the perishable supply chain management.（4）The vehicle routing for the perishable supply chain logistics considering freshness-keeping effort.The vehicle routing and freshness-keeping policy are proposed for the supply chain logistics of perishable products with travel time uncertainty.In order to solve this problem,an optimization model with the goal of minimizing the delivery cost is proposed,in which the cost consists of the time-dependent travel cost,the load-dependent travel cost,the freshness-keeping cost,and the quality loss caused by deterioration.Then,an approximate dynamic programming algorithm（ADP）is proposed to solve it,in which the value function is approximated by a linear combination of state features.In the algorithm,a regularized least-squares linear regression algorithm is used to update the parameters,in which the loss function is characterized with L₂ norm to reduce overfitting.Finally,numerical simulations are conducted to evaluate the performance of the proposed algorithm.The results show that the proposed algorithm is better than the compared algorithm on the key performance indicators,e.g.,the travel time,the travel distances,the average serving quality,etc.,and it is robust to overcome travel time uncertainty.In addition,the proposed model and ADP value iterative algorithms have good applicability with various objectives,such as maximizing profits or minimizing freshness-keeping costs.Aiming at managing perishable products,this thesis provides optimization models,optimization algorithms and control strategies from perspective of the joint ordering,pricing and freshness-keeping effort of the inventory system,the coordination of freshness-keeping effort between retailers and suppliers,and the vehicle routing of the logistics to achieve the optimal performance indicators,and overcome the negative impacts of uncertain factors on the system.The research results have good guiding significance for the actual operation of perishable product inventory system.