In various educational institutes and universities, it has always been quite difficult and a source of headache while constructing no or less conflict timetables especially for a large mass of teachers and students who are divided into different batches, branches and sections. Timetabling is categorized as NP-hard as there exists massive number of combinations and large search space. Not only teachers and students, but also managing other common or general resources such as Labs, Auditoriums, Conference Halls, is not that easy. Thus, this paper proposes an automated timetable generation and resource allocation system which is based on Genetic Algorithm and Constraint Satisfaction Problem techniques.

 The hybrid approach of Genetic Algorithm and Constraint Satisfaction Problem is one of the best ways to demonstrate and solve optimized allocation of resource as it can be implemented in real world. Timetabling is a just subset of our system’s capabilities and effectively minimizes conflicts, saves significant administrative time and provides flexibility and fairness that manual scheduling cannot achieve. It also ensures that specialized resources are utilized in a correct manner. Beyond academic environments the core GA-CSP architecture can be further improved to solve other real world problems that ask for a proper scheduling and optimization.

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