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Marker planning for fabric cutting with sewing schedule constraint in mass customization context |
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| รหัสดีโอไอ | |
| Title | Marker planning for fabric cutting with sewing schedule constraint in mass customization context |
| Creator | Kritsada Puasakul |
| Contributor | Paveena Chaovalitwongse |
| Publisher | Chulalongkorn University |
| Publication Year | 2559 |
| Keyword | Production planning, Production scheduling, Heuristic algorithms, การวางแผนการผลิต, การกำหนดงานการผลิต, ฮิวริสติกอัลกอริทึม |
| Abstract | The objective of this research is to develop heuristics for marker planning problem within a sewing schedule under mass customization production context. In this context, a number of sizes and an amount of demand in each size are varied in a wider range than a mass production system but with lesser total demand. The proposed problem is divided into two subproblems. The first subproblem corresponds with the cost dimension of a marker planning. Hence, the objective is to minimize the total cost related to a number of markers and excessive units. The second subproblem aims to integrate a sewing schedule into marker planning. Therefore, the objective is to minimize a work-in-process inventory workload. The initial solution from the first heuristic is determined by an LP relaxation of marker planning. Then, it is improved by a greedy-based algorithm. This algorithm focuses on reducing an unnecessary plies and adjusting marker patterns. Furthermore, initial solutions are randomized to avoid getting stuck with a local optimum. The second heuristic further improve a first heuristic’s solution by focusing on rearranging marker patterns in order to correspond with a sewing schedule. To measure performance of the proposed heuristics, the first heuristic is tested with many problems. For small-and medium-sized problems, the heuristic can reach to the optimal solutions in all problems while with large-sized problems, heuristic solutions are better than solutions from GA which can reach to optimal solutions as well. The second heuristic is tested with large-sized problems. The second heuristic can perform better than GA method. |
| URL Website | cuir.car.chula.ac.th |
