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Optimal decision making for empty container management at seaport yard

Vinh Ngo Quang, You Sam-Sang You, Long Le Ngoc Bao, Kim Hwan-Seong

LogForum

2023

Vol. 19, no. 1

75--89

Background: In global trade, shipping companies are forced to manage empty containers due to imbalances in international trade activities. For decision-makers, the problems require considering restrictions and an uncertain environment and repositioning or leasing the containers to satisfy the rapidly changing global demands regardless of the epidemic outbreak's impact on the seaport. The proposed approach can help decision-makers manage the empty container in port yards more effectively under market uncertainty by employing the Bellman optimality principle for the stochastic dynamic system. Methods: A stochastic production planning model is employed to cope with uncertainty and unexpected events to ensure a robust management strategy. Ito's formula describes the dynamic model for solving a stochastic differential equation. This paper uses stochastic optimal control theory to deal with efficient empty container management at the port yard. The findings have revealed the effectiveness of the proposed framework, which will provide a decision-making support scheme for efficient port operations. Results: The presented algorithm is realized by a novel approach, employing the Hamilton-Jacobi-Bellman (HJB) equation for optimal stochastic control problems. When comparing the model with and without uncertainty events, the gap is just about 0.04 %, proving the robustness of the proposed model. The results provide a decision support system for port managers when managing the empty container in the seaport yard. Conclusions: The proposed model not only figures out the optimal ordering of empty containers for each cycle but also points out the optimal safety stock level. Using a stochastic optimization approach, decision-makers can implement a strategic management policy to optimize seaport operational costs under market disruptions.

Optimization of stochastic production-inventory model for deteriorating items in a definite cycle using Hamilton-Jacobi-Bellman equation

Hau Bui Minh, Kim Hwan-Seong, Long Le Ngoc Bao, You Sam-Sang

LogForum

2022

Vol. 18, no. 4

397--411

Background: Inventory control is essential for a manufacturer to achieve the desired profit in successful supply chain management. This paper deals with the production-inventory system under the decrease in production rate. The model includes three stages: before the decrease in production, after the decrease in production, and after a period of inventory shortage. Throughout the stages, the stochastic inventory model is always affected by random factors and the deterioration of inventory quality. Method: The article uses the economic order quantity (EOQ) framework to evaluate costs in the production-inventory model. To optimize the manufacturer’s profit with the stochastic factor, Hamilton-Jacobi-Bellman (HJB) equation is presented to find the production rate to make the inventory model to guarantee its intended goals in a determined cycle. Result: Analytical solutions are provided for optimization of the stochastic production-inventory model. Numerical experiments show that inventory level, production rate, and profit over time are based on the optimal initial value of the production rate. Conclusion: The manufacturer’s profit comes from the stages of importing raw materials, processing and producing, storing and supplying items. Finding the initial value of the production rate can make the inventory level and production rate to ensure their desired value and get the target profit within a specified time.