Assemble-to-order;
Simulation optimization;
Production-inventory control policy;
Rationing policy;
Common machine scheduling;
POLICY;
ALGORITHM;
D O I:
10.1007/978-3-030-90421-0_65
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
In this study, we consider an Assemble-to-Order (ATO) system with multiple components, common machines, and multiple customer classes. We first identify the research problems related to all the above-mentioned system features. Thereafter, as the solution methodology, we propose different policies for the described problems. We develop a simulation model of the system and benefit from Genetic Algorithm (GA) metaheuristic that finds near-optimal solutions for inventory control and rationing policies. The simulation model of a quite general ATO system that is integrated with a Genetic algorithm provides solutions for several real-life ATO practices.
机构:
Tsinghua Univ, Sch Econ & Management, Key Res Inst Humanities & Social Sci Univ, Res Ctr Contemporary Management, Beijing 100084, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Ind Engn & Logist Management, Kowloon, Hong Kong, Peoples R China
Xiao, Yongbo
Chen, Jian
论文数: 0引用数: 0
h-index: 0
机构:
Tsinghua Univ, Sch Econ & Management, Key Res Inst Humanities & Social Sci Univ, Res Ctr Contemporary Management, Beijing 100084, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Ind Engn & Logist Management, Kowloon, Hong Kong, Peoples R China
Chen, Jian
Lee, Chung-Yee
论文数: 0引用数: 0
h-index: 0
机构:
Hong Kong Univ Sci & Technol, Dept Ind Engn & Logist Management, Kowloon, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Ind Engn & Logist Management, Kowloon, Hong Kong, Peoples R China