Capacity Planning for Packaging Industry Using Multi-Objective Genetic Algorithm

• Main Authors: Hua, Qi, 華琦
• Other Authors: James C. Chen
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/83082344952462166003

碩士 === 國立清華大學 === 工業工程與工程管理學系 === 104 === Packaging industry is a rapid developing labor-intensive industry. Facing the global trend of integration, intra-industry enterprises compete with each other fiercely. This study develops a capacity planning system (CPS) for packaging plant by using Visual Basic for Application (VBA). It can not only automatically generate order scheduling to meet the delivery of orders, but also balance the workload between machines in the same process. Besides, this study proposes a modified multi-objective genetic algorithm (MOGA) to solve multi-objective order scheduling problem. Two criteria are simultaneously considered for optimization: to minimize the lateness, and to minimize machine workload balance deviation. Design of experiments (DOE) is adopted to validate the performance and analysis of variance (ANOVA) to evaluate the output. This study can provide some reference to packaging plants to make better order scheduling decisions, efficiently reducing lateness and balancing machine workload.