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Harahap , Ryanda Fadillah
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Computer Science & IT Engineering

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The Application of Genetic Algorithm in Construction Project Planning System At Cv. Haza Mulia Engineering Harahap , Ryanda Fadillah; Muliono, Rizki
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 3Spc (2025): Special Issues 2025: Innovations in Predictive Analytics and Sentiment Analy
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i3Spc.14432

Abstract

Project scheduling is a crucial aspect in construction project management that aims to ensure that all tasks are carried out in an optimal sequence to maximize efficiency and reduce completion time. This study has three main objectives: (1) to build a web-based construction project planning system at CV. Haza Mulia Engineering, (2) to apply genetic algorithms to the construction project planning system at CV. Haza Mulia Engineering, and (3) to analyze the performance of genetic algorithms in generating optimal project schedules. This study was motivated by the need to complete a final assignment or thesis and used genetic algorithms as the main method. The research process begins with the identification of tasks and dependencies in a construction project. An initial population consisting of random schedules is generated and evaluated using a genetic algorithm. The selection, crossover, and mutation processes are carried out to gradually produce a new, better population. The fitness of each individual is calculated based on the number of unconnected activity dependencies, and the algorithm stops when the best mutually continuous schedule is found. The main result of this study is a web-based application built using PHP. This application is able to produce more efficient project scheduling compared to conventional methods. The schedule generated by genetic algorithm shows significant reduction in project completion time by minimizing unmet dependencies. The conclusion of this study confirms that the application of genetic algorithm in web-based project planning scheduling can avoid conflicts between activities and make the schedule more structured.
Co-Authors Rizki Muliono