{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T05:38:51Z","timestamp":1778737131922,"version":"3.51.4"},"reference-count":32,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,23]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In this study, a student-based placement model using the A* algorithm is proposed and applied to solve the problem of placing the courses in exam sessions. The application area of the model is midterm and final exams, conducted by the Open Education Faculty. The reason for choosing open education exams for the practice is that the exams are applied across the country and more than 100,000 students participate. The main problem is to obtain a suitable distribution that can satisfy many constraints simultaneously. In the current system, the lessons in the sessions were placed once using the curriculum knowledge. This placement plan is applied in all exams. When the placement is done according to the curriculum information, the courses in the sessions cannot be placed effectively and efficiently due to a large number of common courses and the large number of students taking the exam. This makes the booklets more expensive and the organization more prone to errors. Both the opening of new programs and the increase in the number of students regularly lead to the necessity of placing the classes in sessions dynamically each semester. In addition, to prevent conflicts with the calendars of other central exams, it is necessary to conduct all exams in three sessions. A better solution was obtained by using a different model than the currently used model in the study. With this solution, distribution of the courses of successful students with few courses to all sessions is provided, and difficult courses of unsuccessful students who have a large number of courses were gathered in the same session. This study can support future studies on two issues: the first issue is the approach of using the course that will be taken by most students instead of the courses taught in most departments in the selection of the course to be placed in the booklet. The second issue is to try to find the most suitable solution by performing performance tests on many algorithms whose performance has been determined by many academic studies.<\/jats:p>","DOI":"10.1515\/comp-2022-0237","type":"journal-article","created":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T19:41:54Z","timestamp":1653334914000},"page":"181-190","source":"Crossref","is-referenced-by-count":1,"title":["A student-based central exam scheduling model using A* algorithm"],"prefix":"10.1515","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6741-6268","authenticated-orcid":false,"given":"Mehmet Sinan","family":"Ba\u015far","sequence":"first","affiliation":[{"name":"Atat\u00fcrk University, Open Education Faculty, Department of Business , Erzurum , Turkey"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7824-756X","authenticated-orcid":false,"given":"Sinan","family":"Kul","sequence":"additional","affiliation":[{"name":"Atat\u00fcrk University, Open Education Faculty, Department of Computer , Erzurum , Turkey"}]}],"member":"374","published-online":{"date-parts":[[2022,5,23]]},"reference":[{"key":"2022081707553233571_j_comp-2022-0237_ref_001","doi-asserted-by":"crossref","unstructured":"Z. Ceylan, A. Y\u00fcksel, A. Y\u0131ld\u0131z, and B. \u015eim\u015fak, \u201cS\u0131nav \u00e7izelgeleme problemi i\u00e7in hedef programlama yakla\u015fimi ve bir uygulama,\u201d Erzincan Univ. J. Sci. Technol., vol. 12, no. 2. pp. 942\u2013956, 2019.","DOI":"10.18185\/erzifbed.513981"},{"key":"2022081707553233571_j_comp-2022-0237_ref_002","unstructured":"A. \u00c7oruhlu, S\u0131nav Personel \u00c7izelgeleme Modeli: Gazi \u00dcniversitesi Fen Bilimleri Enstit\u00fcs\u00fc, Y\u00fcksek Lisans Tezi, Ankara, T\u00fcrkiye, 2007."},{"key":"2022081707553233571_j_comp-2022-0237_ref_003","doi-asserted-by":"crossref","unstructured":"B. J. Lovett and L. J. Lewandowski, \u201cTiming and scheduling accommodations,\u201d Testing Accommodations for Students With Disabilities: Research-Based Practice, APA, 2015.","DOI":"10.1037\/14468-000"},{"key":"2022081707553233571_j_comp-2022-0237_ref_004","doi-asserted-by":"crossref","unstructured":"G.Di Pietro, \u201cExam scheduling and student performance,\u201d Bull. Econ. Res., vol. 65, no. 1. pp. 65\u201381, 2013.","DOI":"10.1111\/j.1467-8586.2011.00423.x"},{"key":"2022081707553233571_j_comp-2022-0237_ref_005","doi-asserted-by":"crossref","unstructured":"B. Genc, and B. O\u2019Sullivan, \u201cA Two-Phase constraint programming model for examination timetabling at university college cork,\u201d International Conference on Principles and Practice of Constraint Programming, Cham, Springer, 2020, pp. 724\u2013742.","DOI":"10.1007\/978-3-030-58475-7_42"},{"key":"2022081707553233571_j_comp-2022-0237_ref_006","doi-asserted-by":"crossref","unstructured":"S. Goulas and R. Megalokonomou, \u201cMarathon, hurdling, or sprint? the effects of exam scheduling on academic performance,\u201d BE J. Econ. Anal. Policy, vol. 20, no. 2, 2020.","DOI":"10.1515\/bejeap-2019-0177"},{"key":"2022081707553233571_j_comp-2022-0237_ref_007","unstructured":"F. Bulut and \u0130. F. Ince, \u201cTam Say\u0131 Programlamada A\u00e7g\u00f6zl\u00fc Ve Sezgisel Aramalar \u0130le 0\/1 S\u0131rt \u00c7antas\u0131 Problemine Yeni Bir Bak\u0131\u015f,\u201d Karaelmas Fen. ve M\u00fchendislik Derg., vol. 8, no. 1. pp. 89\u201398, 2018."},{"key":"2022081707553233571_j_comp-2022-0237_ref_008","doi-asserted-by":"crossref","unstructured":"M. Hamedi, \u201cIntelligent fixture design through a hybrid system of artificial neural network and genetic algorithm,\u201d Artif. Intell. Rev., vol. 23, no. 3. pp. 295\u2013311, 2005.","DOI":"10.1007\/s10462-004-7187-z"},{"key":"2022081707553233571_j_comp-2022-0237_ref_009","doi-asserted-by":"crossref","unstructured":"W. Al-Mudhafer and M. Alabbas, \u201cApplication of a hybrid system of genetic algorithm & fuzzy logic as optimization techniques for improving oil recovery in a sandstone reservoirs in Iraq,\u201d In SPE Latin America and Caribbean Petroleum Engineering Conference, OnePetro, 2012.","DOI":"10.2118\/149982-MS"},{"key":"2022081707553233571_j_comp-2022-0237_ref_010","unstructured":"Y. Fukuyama, H. Endo, and Y. Nakanishi, \u201cA hybrid system for service restoration using expert system and genetic algorithm,\u201d In Proceedings of International Conference on Intelligent System Application to Power Systems, IEEE, 1996, pp. 394\u2013398."},{"key":"2022081707553233571_j_comp-2022-0237_ref_011","unstructured":"S. N. Sivanandam, and S. N. Deepa, Introduction to Genetic Algorithms, & Business Media, New York, Springer Science, 2008."},{"key":"2022081707553233571_j_comp-2022-0237_ref_012","doi-asserted-by":"crossref","unstructured":"M. Ayob, A. R. Hamdan, S. Abdullah, Z. Othman, M. Z. A. Nazri, K. A. Razak, et al., \u201cIntelligent examination timetabling software,\u201d Proc. Soc. Behav. Sci., vol. 18, pp. 600\u2013608, 2011.","DOI":"10.1016\/j.sbspro.2011.05.087"},{"key":"2022081707553233571_j_comp-2022-0237_ref_013","unstructured":"C. B. Kalayc\u0131, \u00d6\u011frenci Ba\u015far\u0131s\u0131na Odakl\u0131 S\u0131nav \u00c7izelgeleme Modeli ve Yaz\u0131l\u0131m Uygulamas\u0131: Pamukkale \u00dcniversitesi Fen Bilimleri Enstit\u00fcs\u00fc, Y\u00fcksek Lisans Tezi, Denizli, T\u00fcrkiye, 2008."},{"key":"2022081707553233571_j_comp-2022-0237_ref_014","doi-asserted-by":"crossref","unstructured":"M. Ayob, A. Malik, S. Abdullah, A. Hamdan, G. Kendall, and R. Qu, Solving a practical examination timetabling problem: a case study, pp. 611\u2013624, 2007.","DOI":"10.1007\/978-3-540-74484-9_53"},{"key":"2022081707553233571_j_comp-2022-0237_ref_015","unstructured":"M. F. Acar and M. \u015eevkli, \u201cS\u0131nav \u00c7izelgelemesi \u0130\u00e7in Matematiksel Model Yakla\u015f\u0131m\u0131,\u201d Verimlilik Derg., vol. 1, pp. 75\u201386, 2013."},{"key":"2022081707553233571_j_comp-2022-0237_ref_016","unstructured":"L. K. Bergmann, K. Fischer, and S. Zurheide, \u201cA linear mixed-integer model for realistic examination timetabling problems,\u201d 10th International Conference on the Practice and Theory of Automated Timetabling, pp. 82\u2013101, 2014."},{"key":"2022081707553233571_j_comp-2022-0237_ref_017","doi-asserted-by":"crossref","unstructured":"A. Muklason, A. J. Parkes, E. \u00d6zcan, B. McCollum, and P. McMullan, \u201cFairness in examination timetabling: student preferences and extended formulations,\u201d Appl. Soft Comput., vol. 55, pp. 302\u2013318, 2017.","DOI":"10.1016\/j.asoc.2017.01.026"},{"key":"2022081707553233571_j_comp-2022-0237_ref_018","unstructured":"S. Kadry, and B. Ghazal, \u201cNew Algorithm to Solve Examination Timetable Problem,\u201d Int. J. Adv. Sci. Res., vol. 1, pp. 9\u201318, 2016."},{"key":"2022081707553233571_j_comp-2022-0237_ref_019","doi-asserted-by":"crossref","unstructured":"N. Leite, C. M. Fernandes, F. Mel\u00edcio, and A. C. Rosa, \u201cA cellular memetic algorithm for the examination timetabling problem,\u201d Comp Oper. Res., vol. 94, pp. 118\u2013138, 2018.","DOI":"10.1016\/j.cor.2018.02.009"},{"key":"2022081707553233571_j_comp-2022-0237_ref_020","doi-asserted-by":"crossref","unstructured":"H. Altunay and T. Eren, \u201cA literature review for course scheduling problem,\u201d Pamukkale Uni M\u00fchendislik Bilimleri Derg., vol. 23, no. 1. pp. 55\u201370, 2017.","DOI":"10.5505\/pajes.2016.37233"},{"key":"2022081707553233571_j_comp-2022-0237_ref_021","doi-asserted-by":"crossref","unstructured":"K. Socha, J. Knowles, and M. Samples. \u201cA max-min ant system for the university course time tabling problem,\u201d 3rd International Workshop on Ant Algorithms (ANTS'02), London, UK, pp. 12\u201314, 2002.","DOI":"10.1007\/3-540-45724-0_1"},{"key":"2022081707553233571_j_comp-2022-0237_ref_022","doi-asserted-by":"crossref","unstructured":"S. A. Mirhassani and F. Habibi, \u201cSolution approaches to the course timetabling problem,\u201d Artif. Intell. Rev., vol. 39, no. 2. pp. 133\u2013149, 2013.","DOI":"10.1007\/s10462-011-9262-6"},{"key":"2022081707553233571_j_comp-2022-0237_ref_023","unstructured":"Z. K. \u00d6zt\u00fcrk, E\u011fitimsel Zaman \u00c7izelgeleme Problemleri \u0130\u00e7in \u00c7\u00f6z\u00fcm Yakla\u015f\u0131mlar\u0131 ve Web Tabanl\u0131 Bir Karar Destek Sistemi \u00d6neris, Anadolu \u00dcniversitesi, Doktora Tezi, Eski\u015fehir,T\u00fcrkiye, 2010."},{"key":"2022081707553233571_j_comp-2022-0237_ref_024","unstructured":"R. Yonetani, T. Taniai, M. Barekatain, M. Nishimura, and A. Kanezaki, \u201cPath planning using neural A* search,\u201d In International Conference on Machine Learning. PMLR, pp. 12029\u201312039, 2021."},{"key":"2022081707553233571_j_comp-2022-0237_ref_025","doi-asserted-by":"crossref","unstructured":"M. P. Strub and J. D. Gammell, \u201cAdaptively Informed Trees (AIT*): Fast asymptotically optimal path planning through adaptive heuristics,\u201d In 2020 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 3191\u20133198, 2020.","DOI":"10.1109\/ICRA40945.2020.9197338"},{"key":"2022081707553233571_j_comp-2022-0237_ref_026","doi-asserted-by":"crossref","unstructured":"X. Jiang, Z. Lin, T. He, X. Ma, S. Ma, and S. Li, \u201cOptimal path finding with beetle antennae search algorithm by using ant colony optimization initialization and different searching strategies,\u201d IEEE Access., vol. 8, pp. 15459\u201315471, 2020.","DOI":"10.1109\/ACCESS.2020.2965579"},{"key":"2022081707553233571_j_comp-2022-0237_ref_027","doi-asserted-by":"crossref","unstructured":"Y. Xu, G. Guan, Q. Song, C. Jiang, and L. Wang, \u201cHeuristic and random search algorithm in optimization of route planning for Robot\u2019s geomagnetic navigation,\u201d Computer Commun., vol. 154, pp. 12\u201317, 2020.","DOI":"10.1016\/j.comcom.2020.02.043"},{"key":"2022081707553233571_j_comp-2022-0237_ref_028","doi-asserted-by":"crossref","unstructured":"R. Kong and X. Tong, \u201cDynamic weighted heuristic trust path search algorithm,\u201d IEEE Access., vol. 8, pp. 157382\u2013157390, 2020.","DOI":"10.1109\/ACCESS.2020.3019797"},{"key":"2022081707553233571_j_comp-2022-0237_ref_029","doi-asserted-by":"crossref","unstructured":"S. Kul and M. S. Ba\u015far, \u201cPlacing the courses in question booklets with A* algorithm in central exams,\u201d AJIT-e, vol. 12, no. 45. pp. 29\u201344, 2021.","DOI":"10.5824\/ajite.2021.02.002.x"},{"key":"2022081707553233571_j_comp-2022-0237_ref_030","unstructured":"S. Ayg\u00fcn and M. Ak\u00e7ay, \u201cMatlab Paralel Hesaplama Arac\u0131 \u0130le A* Algoritmas\u0131n\u0131n Rota Planlama \u0130\u00e7in Analizi: Gen\u00e7 M\u00fchendisler Sempozyumu, \u0130stanbul, T\u00fcrkiye, 2015."},{"key":"2022081707553233571_j_comp-2022-0237_ref_031","unstructured":"F. Bulut and \u015e. Suba\u015f\u0131, \u201cMerkezi s\u0131navlar i\u00e7in genetik Algoritmalar ile en iyi oturma plan\u0131,\u201d Dokuz Eyl\u00fcl \u00dcniv. M\u00fchendislik Fak\u00fcltesi Fen. ve M\u00fchendislik Derg., vol. 17, no. 51. pp. 122\u2013137, 2015."},{"key":"2022081707553233571_j_comp-2022-0237_ref_032","unstructured":"R. Inam, A* algorithm for multicore graphics processors. Chalmers University of Technology, Master Thesis, G\u00f6teborg, 2009."}],"container-title":["Open Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/comp-2022-0237\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/comp-2022-0237\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,25]],"date-time":"2024-09-25T19:57:18Z","timestamp":1727294238000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/comp-2022-0237\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,1]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,3,16]]},"published-print":{"date-parts":[[2022,3,16]]}},"alternative-id":["10.1515\/comp-2022-0237"],"URL":"https:\/\/doi.org\/10.1515\/comp-2022-0237","relation":{},"ISSN":["2299-1093"],"issn-type":[{"value":"2299-1093","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,1]]}}}