Intelligent Decision Support Algorithm for Uncertain Inventory Management

• 발행기관: 한국항해항만학회
• 저자명: Le Ngoc Bao Long Sam-Sang You Truong Ngoc Cuong Hwan-Seong Kim
• 간행물 정보: 『한국항해항만학회 학술대회논문집』2023 춘계학술대회논문집, 254~255쪽, 전체 2쪽
• 주제분류: 공학 > 해양공학
• 파일형태: PDF
• 발행일자: 2023.05.04

영문 초록

This paper discovers a robust managerial strategy for a stochastic inventory of perishable products, where the model experiences changing factors including inner parameters and an external disturbance with unknown form. An analytical solution for the optimization problem can be obtained by applying the Hamilton-Bellman-Jacobi equation, however the policy result cannot completely suppress the oscillation from the external disturbance. Therefore, an intelligent approach named Radial Basis Function Neural Networks is applied to estimate the unknown disturbance and provide a robust controller to manipulate the inventory level more effective. The final results show the outstanding performance of RBFNN controller, where both the estimation error and control error are guaranteed in the predefined limit.

키워드

Optimization problem Stochastic inventory model Uncertainty approximation HJB equation RBFNN controller