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SOLVING UNIVERSITY TIMETABLING PROBLEMS BASED ON A MULTI-CONSTRAINT ENVIRONMENT Scientia Research LibraryJournal of Engineering and Technology Research2348 - 0424201755 FERNANDO S. VIRAY JR. Page No. 1-14 1 The key to finding an optimum solution for a gargantuan problem such as the University Timetabling Problem (UTP) which is considered an NP-hard problem is to implement a divide and conquer mechanism. In this research, the sub-problems of UTP are considered and input data, factors, and parameters were classified and organized to model several stages or phases of the solution process. Meta-heuristic approaches were implemented in finding an overall feasible solution to the UTP by initiating a specific AI-based local search and optimization algorithm with little human intervention in every phase of the solution process. Algorithms to be utilized as a part of the meta-heuristics include Tabu Search, Greedy Algorithm, Integer Linear Programming, and Bi-Partite Graph Approach. Simulation results revealed that the proposed multi-stage solution process model, by incorporating multi-constraint inputs, is a promising model when paired with any of the subject algorithms as it significantly aids in finding an optimum solution faster in terms of elapsed time and computation resources. Keywords: Timetabling Problem (TP), University Class Scheduling Problem (UCSP), local search and optimization techniques http://www.scientiaresearchlibrary.com/archive-abs.php?arc=796http://www.scientiaresearchlibrary.com/archive/JETR-2017_5_5_1_14_BD.pdf