Optimum Genetic Algorithm Structure Selection in Pavement Management


	Asian Journal of Applied Sciences
	Year: 2012 \| Volume: 5 \| Issue: 6 \| Page No.: 327-341 DOI: 10.3923/ajaps.2012.327.341

Optimum Genetic Algorithm Structure Selection in Pavement Management

A. Golroo and Susan L. Tighe

Abstract: Pavement management encompasses a wide range of tasks from data collection and data processing to maintenance management and life cycle cost analysis. This study concentrates on maintenance management at a project level and a network level. A decision support system provides optimum maintenance actions over time to enhance the performance of a pavement network and prolong its life span. A heuristic method i.e., Genetic Algorithm is applied to tackle this optimization problem. Due to complexity of the problem, applying an optimum Genetic Algorithm structure results in significant enhancements in the Genetic Algorithm procedure and saves computation time which has not been received enough attention to date by researchers. An experimental design is conducted to investigate the optimum Genetic Algorithm structure for solving a pavement maintenance problem. Since the current Genetic Algorithm software is not suitable to run the experiment, an accurate spreadsheet program has been developed for this purpose to conduct the experiment. Two types of objective functions have been applied: single objective functions (minimizing cost) vs. multiple objective functions (minimizing cost and maximizing benefit).

PDF Fulltext XML References Citation Report Citation

RELATED ARTICLES:

•	A Tool for Compressing Images Based on Genetic Algorithm

•	Optimal Short-term Cascade Reservoirs Operation using Genetic Algorithm

•	Parametric Optimization of an Eight-bar Mechanism of a Wheel Loader Based on Simulation

•	Applying Genetic Algorithm to Fast and Precise Selection of GPS Satellites

How to cite this article:

A. Golroo and Susan L. Tighe, 2012. Optimum Genetic Algorithm Structure Selection in Pavement Management. Asian Journal of Applied Sciences, 5: 327-341.

DOI: 10.3923/ajaps.2012.327.341

URL: https://scialert.net/abstract/?doi=ajaps.2012.327.341

COMMENT ON THIS PAPER

Navigation


		Online First
		Current Issue
		Previous Issues
		Editorial Board
		Submit a Manuscript
		Guide to Authors
		Subscribe to E-alerts

Indexed In


		ASCI-Database
		Asian Digital Library
		Cambridge Scientific Abstract
		Chemical Abstract Services
		Google Scholar

Follow @scialert

Science Alert