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Home  >  Volume 38

21. An Intelligent Fuzzy–Ant Colony Optimization Framework for University Lecture Time Table Scheduling by Robinson S.A., Imianvan A.A. and Inyang U.G Volume 38, pp 147 – 154
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One of the problems faced by university system is lecture timetabling. University lecture timetabling is classified as Non deterministic Polynomial (NP) hard problem because the amount of computational time required of lecture time table increases exponentially with problem size. Over the years various lecture timetables have been developed by using methods like sequential, cluster and meta- heuristics methods .These time tables have been characterized by delay in lectures, inadequate lectures periods, overloading of lecturers with workload per weeks and  clashes of lecture venues . Ant Colony Algorithm (ACO) has been proven as the best algorithm in optimization of timetabling but it cannot handle noisy and imprecise data that are inherent in the lecture time table resources alone. However, this system will Propose a framework for timetable scheduling using Ant Colony optimization (ACO) Algorithm and Fuzzy Logic, formulate and formalize appropriate hard and soft constraints for optimal time table resource allocation and determine the uncertainty on the lecture timetable resources. In order to prevent these weaknesses, fuzzy logic (FL) tool is combined with ACO used to handle uncertainty in the search space by measuring the degree of violation of soft constraints. Hence, a robust framework driven by FL and ACO is developed for effective scheduling of lecture timetable.

Keywords: Ant Colony Optimization, Time table Scheduling, Fuzzy Logic and Hard Constraints, Soft Constraint