運用粒子群聚演最佳化法之橋塔工程

Using Particle Swarm Optimization for Pylon Construction

那桑提(Nadsanti Lertpiriyakamol)

指導教授 ： 張陸滿

國立臺灣大學/工學院/土木工程學研究所/碩士(2011年)

https://doi.org/10.6342/NTU.2011.01028

摘要

無資料

關鍵字

爬模法 ； 粒子群聚演算法 ； 最佳化 ； 模擬 ； 橋塔工程

並列摘要

Construction method using climbing form (sometimes referred to as jump-form, self-climbing or self-lifting) is economical and effective for tall structures such as core walls, lift shaft, stair shafts, silo or bridge piers (or pylons) due to its superior speed and productivity. For cable-stayed bridge construction, the bridge pylon is typically constructed ahead of bridge deck by using climbing form system which comprises the formwork and the working platforms for cleaning, steel fixing, concreting, followed-up or repair works, and self-lifting mechanical system.
Due to the study of simulation technique is very limited to the study of earthworks and a few of precast operations. This study aims to apply the simulation to solve the problem in pylon construction project using climbing formwork technique.

Different combinations of construction methods and varieties in resource utilizations affect the cost and duration in pylon construction project. This objective of this study is to apply particle swarm optimization in combination with simulation technique to establish the framework for solving multiobjective cost/duration optimization in the pylon construction using climbing form technique. The framework consists of optimization module and simulation module. The main activities for pylon construction process are reviewed. The particle swarm optimization module accounts for optimizing seven optimization variables e.g. reinforcement fabrication method, steel frame fabrication method, stressing method, etc. The hybridized particle swarm optimization using variable neighborhood search algorithm is also included for comparison with original particle swarm optimization. The framework can quickly provide a set of near-optimum solutions of the resource utilization combinations.

並列關鍵字

Climbing formwork ； Particle Swarm Optimization ； Simulation ； Pylon

參考文獻

[1] Banks, J. (1998). Handbook of Simulation: Principles, Methodology, Advances, Applications, and Practice, Wiley-Interscience.

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[4] Engelbrecht, A. P. (2007). Computational Intelligence, An Introduction, John Wiley & Sons Ltd.

[6] Hansen, P., and Mladenovic, N. (2001). "Variable neighborhood search: Principles and applications." European Journal of Operational Research, 130(3), 449-467.

[7] Hegazy, T., and Kassab, M. (2003). "Resource Optimization Using Combined Simulation and Genetic Algorithms." Journal of Construction Engineering and Management, 129(6), 698-705.