Abstract
The main objective of apparel factories is to maximize the overall throughput. Since the sewing process is the major bottleneck for most apparel factories, the sewing production lines are not allowed to be idle due to the lack of input materials. To prevent sewing department from idleness, sufficient work-in-process (WIP) inventory of cut pieces must be provided in time by the cutting department. This study aims to schedule the cutting operations with the objective of minimizing their tardiness. The cutting operations of a cutting table can be represented by a two-dimensional Gantt chart, in which horizontal axis represents time line, while vertical axis represents the location on the length of a cutting table. Thus, scheduling the cutting operation of a fabric lay is equivalent to draw a rectangle, whose width is the cutting time of the fabric lay and height is the length of the fabric lay, on a Gantt chart. For cutting scheduling problem, the Gantt charts of cutting tables are two-dimensional bins which are used to contain all cutting activities. Scheduling the cutting operations is similar to the two-dimensional bin packing problems. This study proposes a mixed integer programming model to solve such a cutting schedule problem. In addition, pilot experiments show it takes a long time to solve the mixed integer programming model for a practical-sized problem. Therefore, a heuristic decomposition approach that partitions an original problem into a number of stages is proposed. Each stage is further divided into two phases. The results of the experiments show that the heuristic decomposition approach can yield a satisfactory solution in a short time, especially in large-sized problems.