@article{MAKHILLIJSC20083320921,
    title = {Enhancing Max-Min Ant System for Examination Timetabling Problem},
    journal = {International Journal of Soft Computing},
    volume = {3},
    number = {3},
    pages = {230-238},
    year = {2008},
    issn = {1816-9503},
    doi = {ijscomp.2008.230.238},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2008.230.238},
    author = {F. Djannaty and},
    keywords = {Ant colony optimization,examination timetabling,great deluge algorithm,local search,preprocessing},
    abstract = {Examination Timetabling Problem (ETP) is a real life problem encountered in many academic institutions and has attracted the attention of the Operational Research and Artificial Intelligence research communities since the 1960s. In this study, a variant of Ant Colony Optimization (ACO), the Max-Min Ant System (MMAS) is used to solve the Examination timetabling problem. The key feature of our approach is the combination of a simple local search and MMAS. A preprocessing heuristic is utilized to initially sort the exams. Great Deluge algorithm is used as a local search to improve the constructed solutions by MMAS. We applied our algorithm to a number of test problem data sets. The numerical results obtained from our method shows that the quality of the solutions are better than some or tie the best-published results from the literature, especially on capacitated examination timetabling problem.}
    }