Application of Stochastic Multi-Objective Particle Swarm Optimization for Sustainable Flexible Pavement Design

• Main Authors: Thanh-Son Le, 黎清山
• Other Authors: Jui-Sheng Chou
• Format: Others
• Language: en_US
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/22454296330973884798

碩士 === 國立臺灣科技大學 === 營建工程系 === 98 === Nowadays, global warming, the phenomenon of increasing global surface temperatures, is one of the major concerns in environmental management and protection. All industries, especially, the construction industry, should focus on reducing the impacts of this phenomenon. As a result, engineers face with engaging the construction design that not only balances the conventional tradeoffs between project cost and project duration, but also considers the environmental sensitivities to yield sustainable designs. The aim of this paper is to apply stochastic multi-objective optimization to attain the sustainable design of flexible pavement. This design does not only minimize the construction cost and the project duration, but also the CEs simultaneously under project environment. In order to obtain this goal, a novel multi-objective optimization algorithm based on particle swarm intelligence is proposed and validated with testing problems. Subsequently this algorithm and Monte Carlo simulation are integrated to form a stochastic multi-objective optimization process. A pavement project is used herein to illustrate the case application of proposed model. The results of proposed optimization process are the effective tool for decision maker to choose the most appropriate pavement design.