Design of GAmut-Lssahc: a solver for course timetabling problem
by M. Nandhini, S. Kanmani
International Journal of Mathematics in Operational Research (IJMOR), Vol. 3, No. 6, 2011

Abstract: In this paper, the problem of course timetabling is studied extensively and its constraints are represented using mathematical representation. Analysing the existing GA-based methodologies for solving University Course Timetabling problem, a new method has been proposed probably, which has not yet been attempted for this problem. It employs GA with a variety of proposed MUTation operators (Random-Selection; Adaptive; Goal-Directed) and Local Search of Steepest Ascent Hill Climbing (GAmut-LSsahc) to increase the fitness value and could produce optimal course timetable at the earliest. It was experimentally proved that goal-directed converges 6% faster than adaptive and 10% faster than random-selection mutation.

Online publication date: Thu, 12-Feb-2015

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