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Keywords

genetic algorithm
critical path
Dynamic programming
project network

Abstract

The present study deals with using up-to-date intelligent techniques. We try to utilize the genetic algorithm efficiently and integrate it with the problem of study by designing and applying a genetic algorithm to find the optimal critical path of networks GAOCPN achieving many results, e.g., real time. Accuracy in representing the steps of project execution as a net of nodes and paths has a great role in the accuracy of program results GAOCPN written in C++ version 5.0 under Window. The program was applied on many networks, such as Al-Sarafiya Bridge networks, and the execution time and results were checked and compared with the execution time and results of traditional methods (dynamic programming) and Win_QSB program. The GAOCPN showed accuracy of results in a standard time. Sometimes, it showed optimal results better than those of the traditional methods and it showed results identical to Win_QSB but in standard time.  
https://doi.org/10.33899/csmj.2012.163696
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