Abstract
As global industrial competition intensifies, enterprises can achieve substantial competitive advantages in the supply chain management environment by promptly meeting customer demands and efficiently reducing both supply and demand costs. This paper proposes an inventory model for supply chain optimization that considers uncertain delivery lead times and defective products. Solving the model requires solving a nonlinear mixed-integer problem, which traditionally requires considerable time. Solutions to nondeterministic polynomial-time hard problems with high complexity and difficulty are often obtained using heuristic algorithms. Among these algorithms, genetic algorithms have high efficiency and quality. Therefore, we employed a genetic algorithm to solve the proposed model.
Recommended Citation
Tsao, Hsien-Chung; Chung, Cheng-Chi; Lee, Hsuan-Shih; Lin, Chih-Ping; Tu, Yan-Yun; and Lin, Ssu-Chi
(2023)
"Genetic Algorithm for Solving a Just-In-time Inventory Model With Imperfect Rework Implemented in a Serial Multi-echelon System,"
Journal of Marine Science and Technology: Vol. 31:
Iss.
4, Article 5.
DOI: 10.51400/2709-6998.2712
Available at:
https://jmstt.ntou.edu.tw/journal/vol31/iss4/5
Included in
Fresh Water Studies Commons, Marine Biology Commons, Ocean Engineering Commons, Oceanography Commons, Other Oceanography and Atmospheric Sciences and Meteorology Commons
