| dc.description.abstract | The core objective of this paper is finding optimized methods to mitigate the total
completion time of workers to performce orders early, leading to directly reducing the
cost. This problem is inspired by a real situation observed in a garment manufacturer.
The reduction in production will be a great competitive advantage for the company in
this competitive market. This paper will examine the production schedule of VICT
Garment Factory in Vietnam. Currently, the company conducts the orders based on the
decensding due date of each order. This method is simple to use and is widely used in
production planning. To increase the machine utlization or lower the amount of idle
time, the mathmetical model is used to modify the system and give the optimized
production schedule for the flexible job-shop scheduling problem. The BOM of
products, processing time of workers to complete each operation are collected and
integrated with the model conception (Mixed integer linear programming) to give the
optimized result by running code through CPLEX sofeware. Additionally, I develop a
metaheuristic based on genetic algorithm which is able to efficiently address large
problems by Python code. Based on that information, the company may make some
suggestions to modify or minimize the total cost in the long term. When the problem is
solved by the best result, the sensitive ananlysis is conducted to evaluate methods. As a
result, the company may make plans and some potential strategies to run the business. | en_US |
