Eco Energi

Abstract

The implementation in C++ provides a robust and efficient foundation for Planergy. Leveraging the power of object-oriented programming, the project encapsulates key components such as chromosome representation, fitness evaluation, and genetic operators. The utilization of C++ facilitates scalability, making it adaptable to institutions of varying sizes and complexities. Planergy incorporates a user-friendly interface, allowing administrators and schedulers to input constraints and preferences easily. The algorithm then navigates through the solution space, iteratively refining timetables until convergence to an optimal or near-optimal schedule is achieved. The project's success lies in its ability to adapt to dynamic environments, accommodating changes in preferences or constraints seamlessly. The significance of Planergy extends beyond the immediate benefits of time and effort savings. By automating the timetable generation process, educational institutions can allocate resources more efficiently, reduce scheduling conflicts, and ultimately enhance the overall learning experience. Furthermore, the flexibility of the genetic algorithm enables Planergy to handle a diverse range of scenarios, making it applicable to various scheduling challenges beyond educational institutions.