下載電子全文宣告This thesis is authorized to indicate in-campus access only
You can not download at the moment.
Your IP address is 220.127.116.11
The defense date of the thesis is 2007-09-12
The current date is 2019-07-18
This thesis will be accessible at off-campus not accessible
URN etd-0911107-171823 Statistics This thesis had been viewed 2063 times. Download 22 times. Author Hung-Wei Chang Author's Email Address No Public. Department Information Management Year 2006 Semester 2 Degree Master Type of Document Master's Thesis Language Chinese&English Page Count 99 Title DYNAMIC CRITERIA EVALUATION FOR TOUR SCHEDULING OPTIMIZATION Keyword Tour Planning Optimization Dynamic Evaluation Mechanism Multi Criteria Decision Making Co-evolutionary Genetic Algorithms Co-evolutionary Genetic Algorithms Multi Criteria Decision Making Dynamic Evaluation Mechanism Optimization Tour Planning Abstract People always make decisions in their daily life. However, the most problems are easy to solve. So it can make a property decision. But the more complex problems, the more criteria we have to care about. The decisions become more and more difficult. It forms the Multi-Criteria Decision Making Problems (MCDM). The criteria may be altered by the time. Owing to this reason, it must consider the viewpoint of time into the decision-making process.
This research is based on the dynamic multi-criteria decision-making concept. Adopting co-evolutionary genetic algorithms to solve decision-making problems, it combines the general genetic algorithm with co-evolutionary mechanism to simulate the human thinking to provide the solutions. This paper uses northern Taiwan traveling scheduling for demonstration, and make use of the advantage of genetic algorithms (implicated parallel processing ability and the auto-adjusting capacity) to modify the drawback of traditional methods. After making a serious of experiment to simulate the tour planning that can test the suitable of using co-evolutionary genetic algorithms.
This paper test some tour planning problems and it can find some advantages of co-evolutionary mode. Such as it can not only simulate the thought how people to figure out the problem but also accelerate to find the satisfied answers. So this research provides some reference on decision system developing and design in the future.
Advisor Committee Ying-Hua Chang - advisor
none - co-chair
none - co-chair
Files Date of Defense 2007-06-28 Date of Submission 2007-09-12