Optimization And Control Of Perishable Products Production Under Supply Chain

With the continuous development of the supply chain system,the production planning of manufacturers is faced with more uncertainties.How to control production scientifically and reasonably is one of the most important tasks of production management under supply chain.Perishable products production are often more difficult to control because of their perishable nature.At present,there is a lot of waste of perishable products in our country,which brings cost loss to the manufacturers of perishable products.Therefore,for the manufacturers of perishable products,the key to the production control of enterprises is to ensure the perishable products to complete the production and processing within the production period,and to minimize the production cost.This paper discusses the production and processing of perishable products with a given production period and a fixed production quantity.In the whole production process,the production efficiency changes randomly with the production environment.In this paper,We discuss the control and optimization of production factor input of perishable products under the influence of stochastic environment.That is to control the input of production factors at the control moment,so as to ensure the perishable products to complete the production within a given production period and minimize the input cost of production factors.Firstly,the production model of perishable products under supply chain is established.In the production control,different from the general control mode,this paper proposes a new control mode,which is to choose the decision time epoch arbitrarily during the production period.Specifically,the number of control decision time epoch and the interval between control decision time epoch within the production period can be set arbitrarily.At each decision time epoch,the optimal input of production factors at that moment can be determined according to the current production environment,the remaining production time and the accumulative workload.Due to the randomness of control decision time epoch selection,the production environment will change randomly within each decision interval,resulting in the random change of production efficiency within each decision interval and the uncertainty of production complete workload.Therefore,this paper introduces the distribution function of the accumulative workload,and proposes the Inverse Laplace transform and the Uniformization algorithm to solve the distribution function expression of the accumulative workload.Meanwhile,in order to describe the strict delay problem,Penalty function is introduced to control the production delay.Based on the above methods,the production model is transformed into a Markov Decision Process(MDP)with hybrid states in finite stage.This paper proves that the optimal production strategy is monotonic,that is,the optimal input of production factors is inversely proportional to the remaining production time and directly proportional to the uncompleted workload.Finally,this paper designs a value iteration algorithm based on the monotonicity of production strategy.Compared with the traditional value iterative algorithm,the value iterative algorithm in this paper reduces the computational complexity.This paper makes an empirical analysis of dairy products manufacturer to prove the theoretical results of optimal production strategy and minimum production cost,analyzes the influence of control frequency,production management efficiency and management cost on minimum production cost,and put forward some related management suggestions.In this paper,the traditional control mode is extended in theory.In practical application,this study has a positive significance for the production control optimization,production cost reduction and sustainable development of perishable products manufacturers.