Abstract
Linear construction projects include both discrete linear projects and continuous linear projects. Almost all of the existing simulation models for linear projects are based on the discrete simulation technology and cannot satisfy the modeling requirements of continuous linear projects. There is also a lack of effective optimization tools for continuous linear projects. The available optimization models are either unable to handle complex systems or are formulated only for discrete linear projects. This paper proposes an integrated simulation-GA (genetic algorithm) approach for better planning and scheduling of continuous linear projects. The combined simulation technology will be employed to accurately model different types of activities and relationships. To calculate the production rate of a continuous activity at any point in time , an equation was derived to account for the learning curve effect, and the chaotic function will be used to simulate the uncertainties and the correlations in a time series of points. Decision variables involved in the optimization problem include the number of crews, crew sizes and formations, start times, construction sequences, and slowdown/break rules. A GA model will be developed to help the project manager search for optimal decisions. The solutions generated by the GA will be evaluated though the simulation model.
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