Adapting And Hybrid Ising Harmony Search With Metaheuristic Components For University Course Timetabling
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Date
2010-06
Authors
al-Betar, Mohammed Azmi
Journal Title
Journal ISSN
Volume Title
Publisher
Universiti Sains Malaysia
Abstract
University Course Timetabling Problem (UCTP) is a hard combinatorial scheduling prob-
!em. Harmony Search Algorithm (HSA) is a recent metaheuristic population-based method.
The major thrust of this algorithm I ies in its abiiity to integrate the key components of populationbased
methods and local search-based methods in the same optimisation model. This dissertation
presents a HSA adapted for UCTP. The adaptation involved modifying the HSA operators.
The results were within the range of state of the art. However, some shortcomings in the convergence
rate and local exploitation were identified and addressed through hybridisation with
known metaheuristic components. Three hybridized versions are proposed which are incremental
improvements over the preceding version: (i) Modified Harmony Search Algorithm
(MHSA); (ii) Harmony Search Algorithm with Multi-Pitch Adjusting Rate (HSA-MPAR), and
(iii) Hybrid Harmony Search Algorithm (HHSA). The results werecompared against 21 other
methods using eleven de facto standard dataset of different sizes and complexity. The proposed
hybridized versions achieved the optimal solution for the small datasets, with two best overall
results for the medium datasets. Furthermore, in the large and most complex dataset the
proposed hybrid methods achieved the best result.
Description
Keywords
University Course Timetabling Problem , combinatorial scheduling prob!em.