Single-machine scheduling with both deterioration and learning effects to Minimize Total Weighted Completion Time

• Main Authors: Yu-Chun Wang, 王昱鈞
• Other Authors: Dar-Li Yang
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/2kfw2b

碩士 === 國立虎尾科技大學 === 資訊管理研究所 === 98 === This thesis mainly studies the single machine scheduling problem of works that owns learning effects and deterioration and discusses the operation sequence concerning how to distribute works to machines. And the target of this thesis is to minimize total weighted completion time to make full use of the machine. This study mainly discusses the analysis of its worst-case error bound under the dispatching rules of the weight shortest process time. It conducts performance evaluation in two parts, for one part of works from 6 to 12; it adopts the method of exhaustion Brute-force method to get the optimum solution to the problem to compare it with the WSPT method, and analyzes the error margin between them. And for the other part of works from number 20 to 120, it adopts genetic algorithms to obtain an approximate solution and compare that method with the method. The following results are obtained from the simulation results of execution by the computer, for the sixth to twelfth works, when the deteriorated rate is fixed and the learning effects reduces, although the overall average performance also changes, the extent of difference is small. And for the works from 20 to 120, a solution that is approximate to the WSPT rule can also be obtained when using the genetic algorithms. Because the actual environment of production operation is more complicated than the environment of single machine, in the future, it can be extended into the environments of two-machine or multi-machine scheduling problem that are more complicated as well as other production modes with different learning effects and deteriorated rates.