Three methods to automate the space allocation process in UK universities

Burke, E. K.; Cowling, P.; Landa Silva, J. D.; McCollum, Barry

Abstract

The space allocation problem within UK universities is highly constrained, has multiple objectives, varies greatly among different institutions, requires frequent modifications and has a direct impact on the functionality of the university. As in every optimisation problem, the application of different advanced search methodologies such as local search, metaheuristics and evolutionary algorithms provide a promising way forward. In this paper we discuss three well known methods applied to solve the space allocation problem: hill climbing, simulated annealing and a genetic algorithm. Results and a comprehensive comparison between all three techniques are presented using real test data. Although these algorithms have been extensively studied in different problems, our major objective is to investigate the application of these techniques to the variants of the space allocation problem, comparing advantages and disadvantages to achieve a better understanding of the problem and propose future hybridisation of these and additional methods. © Springer-Verlag Berlin Heidelberg 2001.

Citation

Burke, E. K., Cowling, P., Landa Silva, J. D., & McCollum, B. (2001). Three methods to automate the space allocation process in UK universities. In Evolutionary Multi-Criterion Optimization: 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009. Proceedings (254-273). Springer Verlag. https://doi.org/10.1007/978-3-642-01020-0_38

• Publication Date: Jan 1, 2001
• Deposit Date: Feb 10, 2020
• Publisher: Springer Verlag
• Pages: 254-273
• Series Title: Lecture Notes in Computer Science
• Series Number: 5467
• Book Title: Evolutionary Multi-Criterion Optimization: 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009. Proceedings
• ISBN: 978-3-642-01019-4
• DOI: https://doi.org/10.1007/978-3-642-01020-0_38
• Public URL: https://nottingham-repository.worktribe.com/output/3088203
• Publisher URL: https://link.springer.com/chapter/10.1007%2F978-3-642-01020-0_38