Multiple Objectives, Job Shop, Parallel-Machine Scheduling-Applying the Ant Colony Optimization Algorithm

• Main Authors: Zhong Cheng Zhi, 鍾承志
• Other Authors: Chang Ping Teng
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/86285044016953575449

碩士 === 東海大學 === 工業工程與經營資訊學系 === 92 === It was to regard single objective as scheduling on the foundation that a performance was weighted to study in the past. But general production of manufacturing environment scheduling problem that a single objective can’t be satisfied, it’s consider with many view of multiple objectives in the really world, and conflict with each other between the objectives. And the most scheduling research of multiple objectives at present, only consider manufacturing performance factor. These factors are belonging to quantitative factors. In fact, scheduling environment needs to consider including some about the qualitative factors of the organization. Traditional job shop scheduling mode contain multi-steps single machine of productive environment only, however the mode of production of the parallel-machine has already been applied to every kinds of industries extensively at present, a lot of production in job shop or flow shop utilize parallel-machine to increase capacity, lower the work station load of the bottleneck, and reduce the postpone time of due date. We plan to be based on job shop scheduling in this research, put the parallel-machine, allow the lot splitting of job, make the job operating at several machine meanwhile, and shorten the completion time of operation. For closer to the realistic situation in addition, making the machine being produced continuously in succession, the activity of job that will be adjusted while studying, and making the process time of the same sub-lot operation being tried one’s best to closer. In addition system equips to consider to scheduling performance index of multiple objectives at the same time, and also considers quantitative factor and production scene of performance, and the company strategy factors are included to form a really full of multiple objectives in order to be suitable for the production environment of changeable and high competition today. Depending on above mentioned problems with the increase scale of complexity, if we want to use the method of the optimization to solve, it’s exactly one of the excellent optimization methods while developing at present that the ant algorithm (Ant Colony Optimization, is abbreviated as ACO), have already received the affirmation of the extensive scholar gradually in trying to get the best ability to solve of the whole. So my research is based on Ant Algorithm, wishing to develop a system that can deal with multiple objectives scheduling problems.