[1] McCollum, B. (2006). A perspective on bridging the gap between theory and practice in university timetabling. International conference on the practice and theory of automated timetabling (pp. 3–23). Springer.
[2] Ritzman, L., Bradford, J., & Jacobs, R. (1979). A multiple objective approach to space planning for academic facilities. Management science, 25(9), 895–906. DOI:10.1287/mnsc.25.9.895
[3] Benjamin, C. O., Ehie, I. C., & Omurtag, Y. (1992). Planning facilities at the university of missouri-rolla. Interfaces, 22(4), 95–105. DOI:10.1287/inte.22.4.95
[4] Ülker, Ö., & Landa-Silva, D. (2010). A 0/1 integer programming model for the office space allocation problem. Electronic notes in discrete mathematics, 36(C), 575–582. DOI:10.1016/j.endm.2010.05.073
[5] Burke, E. K., Cowling, P., Landa Silva, J. D., & McCollum, B. (2001). Three methods to automate the space allocation process in UK universities. Practice and theory of automated timetabling III: third international conference, PATAT 2000 Konstanz, Germany, August 16–18, 2000 Selected Papers 3 (pp. 254-273). Springer Berlin Heidelberg. DOI: 10.1007/3-540-44629-x_16
[6] Lopes, R., & Girimonte, D. (2010). The office-space-allocation problem in strongly hierarchized organizations. European conference on evolutionary computation in combinatorial optimization (pp. 143–153). Springer.
[7] Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671–680. DOI:10.1126/science.220.4598.671
[8] Ülker, Ö., & Landa-Silva, D. (2012). Evolutionary local search for solving the office space allocation problem. 2012 IEEE congress on evolutionary computation, CEC 2012 (pp. 1–8). IEEE.
[9] Awadallah, M. A., Khader, A. T., Al-Betar, M. A., & Woon, P. C. (2012). Office-space-allocation problem using harmony search algorithm. Neural information processing: 19th international conference, ICONIP 2012, Doha, Qatar, November 12-15, 2012, proceedings, part II 19 (pp. 365–374). Springer.
[10] Burke, E. K., Silva, J. D. L., & Soubeiga, E. (2005). Multi-objective hyper-heuristic approaches for space allocation and timetabling. Metaheuristics: progress as real problem solvers, 129–158. https://link.springer.com/chapter/10.1007/0-387-25383-1_6
[11] Burke, E. K., Cowling, P., & Silva, J. L. (2001). Hybrid population-based metaheuristic approaches for the space allocation problem. Proceedings of the 2001 congress on evolutionary computation (IEEE Cat. No. 01TH8546) (Vol. 1, pp. 232-239). IEEE.
[12] Burke, E. K., Cowling, P., Landa Silva, J. D., & Petrovic, S. (2001). Combining hybrid metaheuristics and populations for the multiobjective optimisation of space allocation problems. Proceedings of the 2001 genetic and evolutionary computation conference (GECCO 2001) (pp. 1252-1259). https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=039848a7e16c3a378b
34c15f6fa02f380fe6e0f0
[13] Landa-Silva, D., & Burke, D. K. (2007). Asynchronous cooperative local search for the office-space-allocation problem. INFORMS journal on computing, 19(4), 575–587. DOI:10.1287/ijoc.1060.0200
[14] Bashirzadeh, M., Daneshvar, S., & Azarmir, N. (2014). Determining the inefficient space and ranking of DMUs with undesirable outputs. Journal of applied research on industrial engineering, 1(1), 1–11.
[15] Bolaji, A. L., Khader, A. T., Al-Betar, M. A., & Awadallah, M. A. (2014). University course timetabling using hybridized artificial bee colony with hill climbing optimizer. Journal of computational science, 5(5), 809–818.
[16] Bolaji, A. L. A., Khader, A. T., Al-Betar, M. A., & Awadallah, M. A. (2015). A hybrid nature-inspired artificial bee colony algorithm for uncapacitated examination timetabling problems. Journal of intelligent systems, 24(1), 37–54. DOI:10.1515/jisys-2014-0002
[17] Karaboga, D. (2005). An idea based on honey bee swarm for numerical optimization. http://mf.erciyes.edu.tr/abc/pub/tr06_2005.pdf
[18] Bolaji, A. L., Khader, A. T., Al-Betar, M. A., & Awadallah, M. A. (2013). Artificial bee colony algorithm, its variants and applications: a survey. Journal of theoretical and applied information technology, 47(2), 434–459.
[19] Karaboga, D., Gorkemli, B., Ozturk, C., & Karaboga, N. (2014). A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artificial intelligence review, 42(1), 21–57. DOI:10.1007/s10462-012-9328-0
[20] Bolaji, A. L., Khader, A. T., Al-Betar, M. A., & Awadallah, M. A. (2012). Artificial bee colony algorithm for solving educational timetabling problems. International journal of natural computing research, 3(2), 1–21.
[21] Azeeta, A., Misra, S., Odusami, M., Peter, O. U., & Ahuja, R. (2021). An intelligent student hostel allocatıon system based on web applications. Recent innovations in computing: proceedings of ICRIC 2020 (pp. 779–791). Springer.
[22] Bolaji, A. L., Michael, I., & Shola, P. B. (2017). Optimization of office-space allocation problem using artificial bee colony algorithm. Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics) (Vol. 10385 LNCS, pp. 337–346). Springer International Publishing.
[23] Ishichi, K., Ohmori, S., Ueda, M., & Yoshimoto, K. (2019). Shelf-space allocation model with demand learning. Operations and supply chain management, 12(1), 24–30. DOI:10.31387/oscm0360219
[24] Bolaji, A. L. aro, Bamigbola, A. F., & Shola, P. B. (2018). Late acceptance hill climbing algorithm for solving patient admission scheduling problem. Knowledge-based systems, 145, 197–206.
[25] Mtonga, K., Twahirwa, E., Kumaran, S., & Jayavel, K. (2021). Modelling classroom space allocation at university of Rwanda-a linear programming approach. Applications and applied mathematics: an international journal (AAM), 16(1), 40. https://digitalcommons.pvamu.edu/aam/vol16/iss1/40/
[26] Hasan Zadeh, R., & Alizade, S. (2019). Multi-location logistics in relief with regard to urban infrastructure. Journal of decisions and operations research, 4(3), 232–245. (In Persian). https://www.journal-dmor.ir/article_96789_en.html?lang=fa
[27] Rashidi, H. (2020). A Mathematical optimization model for allocating student dormitories in corona-living conditions. Journal of decisions and operations research, 5(2), 188–203. (In Persian). https://www.journal-dmor.ir/article_120042.html?lang=en
[28] Lotfi, R., Pilehforooshha, P., & Karimi, M. (2023). A multi-objective optimization model for school location-allocation coupling demographic changes. Journal of spatial science, 68(2), 225–244.
[29] Kakkar, M. K., Singla, J., Garg, N., Gupta, G., Srivastava, P., & Kumar, A. (2021). Class schedule generation using evolutionary algorithms. Journal of physics: conference series (Vol. 1950, No. 1, p. 012067). IOP Publishing. DOI: 10.1088/1742-6596/1950/1/012067
[30] Raja Murugadoss, J., & Krishna Kishore, K. (2020). Effectiveness of E-learning in rural India and significance of self-directed learning. International journal of advanced science and technology, 29(6), 6015–6020.
[31] Razmjooei, V., Mahdavi, I., & Gutmen, S. (2022). A hybrid multi-objective algorithm to solve a cellular manufacturing scheduling problem with human resource allocation. Journal of applied research on industrial engineering, 9(2), 272–287.
[32] Schreck, J., Baretton, G., & Schirmacher, P. (2020). Situation of the German university pathologies under the constraints of the corona pandemic—evaluation of a first representative survey. Pathologe, 41(4), 400–405.
[33] Rudd, K., Foderaro, G., Zhu, P., & Ferrari, S. (2017). A generalized reduced gradient method for the optimal control of very-large-scale robotic systems. IEEE transactions on robotics, 33(5), 1226–1232.