Applying Double Evolution of Strategy to Unrelated Parallel Machine Scheduling Problems with Lot Streaming

• Main Authors: WANG, CHUN-HSING, 王春興
• Other Authors: LOW, CHIN-YAO
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/5bf969

碩士 === 國立雲林科技大學 === 工業工程與管理系 === 106 === 　　This paper focuses on the multi-stage of flow shop scheduling with lot streaming and parallel machine. In the batch of lot streaming have an equal lot streaming and non-equal lot streaming, due to the non-equal lot streaming similar continuous problems that can be divided into an unlimited number of combinations, so this paper adopted the equal lot streaming conditions. Parallel machine is divided into the identical parallel machine and unrelated parallel machine, most scholars in the past explore the identical parallel machine, but in fact the vast majority of processed are based on unrelated parallel machine processing. Therefore, this paper considers unrelated parallel machine as the background. 　　Flow shop scheduling has proved to be an NP-hard problem, and the addition of lot streaming and unrelated parallel machine will make the problem more complicated. This paper builds mathematical integer programming models and small-scale example and proves them using mathematical programming software. After establishing the mathematic model basement, this paper will construct the algorithm of double evolution strategy to solve the problem. The double evolution of strategy will use Discrete Differential Evolution and Particle Swarm Optimization as the basis, and use the master-apprentice sharing mechanism to achieve the goal of improving the efficiency of the solution, then used the Taguchi experimental method to find the best combination of parameters, and finally to different of batch size to test and analysis.