![]() The GA generates the population by randomly sampling from the dataset, and ensures that a good enough population with diverse chromosome are generated so that the crossovers and mutations may produce good solutions. The final individual is an array of such genes Population Generation ![]() The GA encodes the problem domain as follows: Each chromosome has a number of genes. The problem is to find the timetable that can minimize all the constraints of the problem. The dataset provided many clashes in the Course Registrations. The dataset used for this problem consists of CSV files for Students, Course, Course Registrations, and Teachers. The Program runs a Genetic Algorithm to find the timetable of the examination, alongside student seating plans, room allocations, and faculty invigilation allottment. This allows the faculties to enter the Couse Details, Teacher Details, and Students Registered for examination. A Genetic Algorithm based Timetable Schedule Generator, that can be used by University and College Management.
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