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New Bounds for Office Space Allocation using Tabu Search

Published: 20 July 2016 Publication History

Abstract

The Office Space Allocation problem is a combinatorial optimization problem which focuses into determining the way to assign spaces to entities in order to optimize the use of available space in an organization. This allocation process considers a set of preferences, constraints and requirements. In this paper we propose a metaheuristic approach that includes a construction step and an improvement step, based on Greedy and Tabu Search techniques respectively. Here, we propose a construction method specially designed to deal with the misused space and hard/soft constraints of the problem. Then, Tabu Search performs a fast analysis that allows it to find good quality neighborhoods to analyze. We used an automated tuning method to determine the best parameter values for the entire set of benchmarks. Results show that our approach was able to obtain new lower bounds for seven problem instances.

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E. K. Burke, P. I. Cowling, J. D. L. Silva, and B. McCollum. Three Methods to Automate the Space Allocation Process in UK Universities. In Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III, pages 254--276, London, UK, 2001. Springer-Verlag.
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cover image ACM Conferences
GECCO '16: Proceedings of the Genetic and Evolutionary Computation Conference 2016
July 2016
1196 pages
ISBN:9781450342063
DOI:10.1145/2908812
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 20 July 2016

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Author Tags

  1. greedy
  2. local search
  3. office space allocation
  4. tabu search

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GECCO '16
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GECCO '16: Genetic and Evolutionary Computation Conference
July 20 - 24, 2016
Colorado, Denver, USA

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GECCO '16 Paper Acceptance Rate 137 of 381 submissions, 36%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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