A genetic algorithm based multiple objective decision making model to explore the sustainable city bus

• Main Authors: WEI-JHONG LIN, 林維中
• Other Authors: James Liou
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/49f88z

碩士 === 國立臺北科技大學 === 工業工程與管理系碩士班 === 102 === The concept of sustainable development introduces into transport department which is sustainable transport as the main development strategy for the transport department in the various countries. Sustainable transportation which includes environment, economy and society is a Multi-objective programming problem. The problem can obtains many Pareto solutions as feasible solutions through a variety of algorithm which provide decision makers to select, but decision makers directly select the ideal solution based on their own experiences and preferences in the case of many feasible solutions is difficult. Therefore, this research uses a hybrid decision making model to combine multiple objective genetic algorithm and multiple attribute decision making. Multi-objective genetic algorithms can handle complex multi-objective optimization problem to obtain Pareto solutions; multi-attribute decision making can find the preferences of different groups of decision makers and sort the Pareto solutions which helps decision maker selects a preferenced solution to carry out. In order to verify the validity of model, one example of Taoyuan city buses is used to discuss the optimization problem of sustainable city buses. Through experts questionnaires consider the views obtained from government and academic institutions, we compare the results of the hybrid decision making model and the fuzzy multi-objective programming method. The results show that city bus''s capacity is the most important evaluation criteria of experts and two model''s best compromise solutions are similar. It shows the effectiveness of the proposed model.