Research on Distribution and Inventory Cooperation of Agricultural Means Supply Chain

This paper constructed a biobjective model based on the total cost and time satisfaction to provide a desirable solution to the distribution and inventory cooperation of agricultural means supply chain. The model simulated how the distribution center and retailers collaborate to meet the needs of the order customer in the random lead time and out-of-stock loss costs. By the features of the model, the biobjective genetic algorithm was improved based on elitism selection, aiming to improve the quality of noninferior solution in biobjective model. Finally, the influence degree of the lead time of delivery, unit inventory cost, and unit transport cost on the total cost of the system was quantified through the analysis of examples and sensitivity of model parameters. This research has provided valuable new insights into the distribution and inventory coordination of supply chain.

A Joint Optimization Model of s , S Inventory and Supply Strategy Using an Improved PSO-Based Algorithm

This paper mainly discussed the problem of a multiechelon and multiperiod joint policy of inventory and supply network. According to the random lead time and customers’ inventory demand, the s , S policy was improved. Based on the multiechelon supply network and the improved, the dynasty joint model was built. The supply scheme in every period with the objective of minimum total costs is obtained. Considering the complexity of the model, the improved particle swarm optimization algorithm combining the adaptive inertia weight and grading penalty function is adopted to calculate this model and optimize the spare part problems in various environments.

Supply Chain Model for Expiring Items Following Ramp-Type Demand With Stochastic Lead Time Under Crisp and Fuzzy Environment

Supply chain models with deteriorating items, season pattern demand, expiration and uncertain lead time, though common in practice; had received little attention from researchers. In this article, the authors proposed a collaborative system with ramp type seasonal pattern demand rate for expiring items with supplier's random lead time under crisp and fuzzy environment considering the effect of inflation and time value of money. For the seasonal kind of items, demand rate follows the combination of increasing-steady-decreasing demand patterns. A supplier's lead time is a stochastic function of his managing cost; thus, the extra costs incurred on the retailer due to the uncertainty in lead time in terms of shortages costs and lost sales costs are owed by the supplier. Numerical examples are cited to illustrate the results and its significant features. Finally, to study the effect of change of parameters sensitivity analysis is presented and necessary observations are made.

An Inventory Model for Deteriorating Drugs with Stochastic Lead Time

Inventory management of deteriorating drugs has attracted considerable attention recently in hospitals. Drugs are a kind of special product. Two characteristics of some drugs are the shorter shelf life and high service level. This causes hospitals a great deal of difficulty in inventory management of perishable drugs. On one hand, hospitals should increase the drug inventory to achieve a higher service level. On the other hand, hospitals should decrease the drug inventory because of the short shelf life of drugs. An effective management of pharmaceuticals is required to ensure 100% product availability at the right time, at the right cost, in good conditions to the right customers. This requires a trade-off between shelf-life and service level. In addition, many uncontrollable factors can lead to random lead time of drugs. This paper focuses on deteriorating drugs with stochastic lead time. We have established a stochastic lead time inventory model for deteriorating drugs with fixed demand. The lead time obeyed a certain distribution function and shortages were allowed. This model also considered constraints on service level, stock space and drug shelf life. Through the analysis of the model, the shelf life of drugs and service level were weighted in different lead time distributions. Empirical analysis and sensitivity analysis were given to get reach important conclusions and enlightenment.