1. [1] Burke E.K., Cowling P., Landa Silva J.D., McCollum B. (2000), Three Methods to Automate the Space Allocation Process in UK Universities, Proceedings of the 3rd International Conference on the Practice and Theory of Automated Timetabling, PATAT 2000, Konstanz, Germany, pp. 374-393. 2. [2] Pereira R., Cummiskey K., Kincaid R.(2010), Office Space Allocation Optimization, Proceedings of the 2010 IEEE Systems and Information Engineering Design Symposium University of Virginia, Charlottesville, VA, USA, April 23. [ DOI:10.1109/SIEDS.2010.5469670] 3. [3] Ritzman, L., J. Bradford and R. Jacobs, (1980), A multiple objective approach to space planning for academic facilities, Managament Science 25, pp. 895–906. [ DOI:10.1287/mnsc.25.9.895] 4. [4] Benjamin, C., I. Ehie and Y. Omurtag, (1992), Planning facilities at the university of missourirolla, Interfaces 22, pp. 94–105. [ DOI:10.1287/inte.22.4.95] 5. [5] Giannikos, J., E. El-Darzi and P. Lees, (1995), An integer goal programming model to allocate offices to staff in an academic instituition, Journal of the Operational Research Society 46, pp. 713–720. [ DOI:10.1057/jors.1995.101] 6. [6] Burke, E. K., J. D. Landa Silva and E. Soubeiga, (2005), Multi-objective hyper-heuristic approaches for space allocation and timetabling, in: T. Ibaraki, K. Nonobe and M. Yagiura, editors, Meta-heuristics: Progress as Real Problem Solvers, Selected Papers from the 5th Metaheuristics International Conference, pp. 129–158. [ DOI:10.1007/0-387-25383-1_6] 7. [7] Burke E.K., Cowling P., Landa Silva J.D., McCollum B., (2001), HYBRID POPULATION-BASED METAHEURISTIC APPROACHES FOR THE SPACE ALLOCATION PROBLEM, Proceedings of the 2001 IEEE congress on evolutionary computation Seoul, Korea, May 27-30. [ DOI:10.1109/CEC.2001.934394] 8. [8] Landa Silva J.D., Burke E.K., (2007), Asynchronous Cooperative Local Search for the Office-Space-Allocation Problem, INFORMS Journal on Computing Vol. 19, No. 4, pp. 575–587 issn 1091-9856 _eissn 1526-5528 _07 _1904 _0575. 9. [9] R. Kincaid, R. Gates, and R. Gage., (2007), Space allocation optimization at nasa langley research center. In Proceedings of the Seventh Metaheuristics International Conference, Montreal, Canada, June 25-30. 10. [10] Talbi, El-Ghazali, Metaheuristics: From Design to Implementation, John Wiley and sons(2009). [ DOI:10.1002/9780470496916] 11. [11] Biesmeijer, J.C., Seeley, T.D., (2005),The Use of Waggle Dance Information by Honey Bees throughout Their Foraging Careers, Behavioral Ecology and Sociobiology, 59(1), 133-142. [ DOI:10.1007/s00265-005-0019-6] 12. [12] Zeng, F., Decraene, J., Yoke Hean Low, M., Hingston, P., Cai, W., Zhou, S., Chandramohan, M., (2010), Autonomous Bee Colony Optimization for Multi-objective Function, In Proceedings of the 2010 IEEE World Congress on Computational Intelligence, pp. 1-8, 18-23, Barcelona, Spain. [ DOI:10.1109/CEC.2010.5586057] 13. [13] Teodorovic, D., Davidovic, T., Selmic, M., (2011), Bee Colony Optimization: The Applications Survey, ACM Transactions on Computational Logic. 14. [14] D.T. Pham, A. Ghanbarzadeh, E. Koç, S. Otri, S. Rahim, M. Zaidi (2006),Manufacturing Engineering Centre, Cardiff University, UK The Bees Algorithm – A Novel Tool for Complex Optimisation Problems, Intelligent Production Machines and Systems pp. 454-459. 15. [15] Zahraee, B., Hosseini, M., (2009), Genetic Algorithm And Engineering Optimization, Gotenberg, Tehran. 16. [16] Bazzazi, M., Safaei, N., Javadian, N. (2009), A genetic algorithm to solve the storage space allocation problem in a container terminal, Computers & Industrial Engineering 56 (2009) 44–52 [ DOI:10.1016/j.cie.2008.03.012] 17. [17] Taghaddos, H., Hermann, U., AbouRizk, S., AbouRizk, Y., (2010), Simulation-based Scheduling of Modular Construction using Multi-agent Resource Allocation, 2010 Second International Conference on Advances in System Simulation. [ DOI:10.1109/SIMUL.2010.36] 18. [18] LIU, Y., KANG, H., ZHOU, P., (2010), Fuzzy Optimization of Storage Space Allocation in a Container Terminal, J. Shanghai Jiaotong Univ. (Sci.), 2010, 15(6): 730-735. [ DOI:10.1007/s12204-010-1077-0] 19. [19] Quijano, N., Passino, K., (2010), Honey bee social foraging algorithms for resource allocation: Theory and application, Engineering Applications of Artificial Intelligence 23 (2010) 845–861. [ DOI:10.1016/j.engappai.2010.05.004] 20. [20].Quijano,N.,Passino,K.M.,2007.Theidealfreedistribution:theoryandengineering application. IEEETransactionsonSystems,Man,andCybernetics—Part B37 (1), 154–165. 21. [21] R. Akbari, A. Mhammadi, K. Ziarati, "A Novel Bee Swarm Optimization Algorithm For Numerical Function Optimization," communications in Nonlinear Science and Numerical Simulation, doi: 10.1016/j. cnsns.2009.11.003. 22. [22] D. Karaboga, B. Basturk, "A Powerful and Efficient Algorithm for Numerical Function Optimization : Artificial Bee Colony (ABC) Algorithm," Journal of Global Optimization, vol. 39, Nov. 2007, pp. 459-471. [ DOI:10.1007/s10898-007-9149-x] 23. [23] Teodorovic, D., Lucic, P., et al. (2006). Bee colony optimization: Principles and applications. In Neural network applications in electrical engineering, 2006 (NEUREL 2006) (pp. 151–156). Belgrade. [ DOI:10.1109/NEUREL.2006.341200]
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