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Evolutionary local search for solving the office space allocation problem

Ulker, Ozgur; Landa-Silva, Dario

Authors

Ozgur Ulker



Abstract

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.

Citation

Ulker, O., & Landa-Silva, D. (2012). Evolutionary local search for solving the office space allocation problem

Conference Name 2012 IEEE Congress on Evolutionary Computation (CEC 2012)
End Date Jun 15, 2012
Publication Date Jun 1, 2012
Deposit Date Mar 7, 2016
Publicly Available Date Mar 7, 2016
Peer Reviewed Peer Reviewed
Keywords Space allocation, Hybrid evolutionary algorithms, Hybrid metaheuristics, Local search
Public URL http://eprints.nottingham.ac.uk/id/eprint/32128
Publisher URL http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6253009
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf
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

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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