Evolutionary local search for solving the office space allocation problem

Ulker, Ozgur and Landa-Silva, Dario (2012) Evolutionary local search for solving the office space allocation problem. In: 2012 IEEE Congress on Evolutionary Computation (CEC 2012), 10-15 June 2012, Brisbane, Australia.

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Office Space Allocation (OSA) is the task of correctly allocating the spatial resources of an institution to a set of entities by minimising the wastage of space and the violation of additional constraints. In this paper, an evolutionary local search algorithm is presented to tackle this problem. The evolutionary components of the algorithm include standard crossover and mutation operators and a relatively small population of individuals. The offspring produced by the evolutionary operators are subjected to a short but intense local search process. A very fast cost calculation method tailored for searching a large section of the search space is implemented. Extensive experimentation is carried out related to several parameters of the algorithm: the mutation rate, the population size, the length of the local search procedure after each mutation, hence the balance between the evolutionary and the local search stages, and the level of greediness of the local search process. The final results on 72 different data instances show that this hybrid evolutionary algorithm is very competitive with an integer programming model.

Item Type: Conference or Workshop Item (Paper)
Additional Information: 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Keywords: Space allocation, Hybrid evolutionary algorithms, Hybrid metaheuristics, Local search
Schools/Departments: University of Nottingham UK Campus > Faculty of Science > School of Computer Science
Depositing User: Landa-Silva, Dario
Date Deposited: 07 Mar 2016 14:23
Last Modified: 13 Sep 2016 14:56
URI: http://eprints.nottingham.ac.uk/id/eprint/32128

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