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Tournament scheduling using genetic algorithm / James Emman Coralde, [and 3 others].

By:

Coralde, James Emman [author.]

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Material type: Text

TextDescription: 94 leavesContent type:

text

Media type:

unmediated

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volume

Dissertation note: Undergraduate Theses (BSCS) - Computer Science Camarines Sur Polytechnic Colleges, 2023. Abstract: The Tournament Scheduling's main task is to generate team scheduling using a genetic algorithm. Offline, the system is a web-based prototype. It runs in the browser and generates a schedule based on the team selected until the best of all teams is determined. The system's goal is to make it easy and accurate for each player and committee to reconcile to develop a sense of team in every tournament or sports event. The study also improve proper evaluation in every game and be smoothly organized to determine the flow and process after the game's result. Based on the information acquired at barangay Siramag Balatan, Camarines Sur. The prototype scored a 0.9, or 90 percent accuracy, and a 0.78, or 78 percent time efficiency, indicating that the facilitators were satisfied with both the accuracy and time efficiency of the prototype. Overall, the facilitators gave the prototype positive feedback. The study supported the claim that the genetic algorithm is efficient and precise for scheduling tournaments.

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Item type	Current library	Shelving location	Call number	Status	Date due	Barcode
Unpublished Materials	Main Library	Undergraduate Thesis Section	UTH BSCS C810t 2023 (Browse shelf(Opens below))	Not for loan		006060UM

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Undergraduate Theses (BSCS) - Computer Science Camarines Sur Polytechnic Colleges, 2023.

Includes bibliographical references.

The Tournament Scheduling's main task is to generate team scheduling using a genetic algorithm. Offline, the system is a web-based prototype. It runs in the browser and generates a schedule based on the team selected until the best of all teams is determined. The system's goal is to make it easy and accurate for each player and committee to reconcile to develop a sense of team in every tournament or sports event. The study also improve proper evaluation in every game and be smoothly organized to determine the flow and process after the game's result. Based on the information acquired at barangay Siramag Balatan, Camarines Sur. The prototype scored a 0.9, or 90 percent accuracy, and a 0.78, or 78 percent time efficiency, indicating that the facilitators were satisfied with both the accuracy and time efficiency of the prototype. Overall, the facilitators gave the prototype positive feedback. The study supported the claim that the genetic algorithm is efficient and precise for scheduling tournaments.

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