Abstract
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.
Highlights
As an important foundation of product maintenance, the research on spare parts in product maintenance is increasingly applied in industrial and military fields
Considering the diversity and complexity of the current supply model, the traditional particle swarm optimization (PSO) algorithm solves this kind of model problem for a long time and cannot obtain the result even
The multiperiod and multiechelon supply network is built, and the ðs, SÞ policy is improved by the random lead time and different customers’ maximum inventory
Summary
As an important foundation of product maintenance, the research on spare parts in product maintenance is increasingly applied in industrial and military fields. The researchers are more interested in the joint optimization of spare part inventory and supply process. In the project of joint optimization of inventory and supply, researchers focus on balancing transportation costs and breakdown losses caused by insufficient inventory based on satisfying demand and determining the supply lead time, to achieve the purpose of maximizing benefits. The joint optimization in this paper can calculate the specific delivery time of each customer by optimizing the supply distribution process. The system optimizes the supply distribution process by adjusting the quantity of spare parts transporting between different nodes. The rest of this paper is arranged as follows: Section 2 outlines spare part supply, inventory policy, and joint optimization.
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