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Details of Grant 

EPSRC Reference: GR/T26115/01
Title: Adaptive Multi-Objective Heuristic and Meta-heuristic Approaches to Space Allocation
Principal Investigator: Burke, Professor EK
Other Investigators:
Medjdoub, Professor B Kendall, Professor G Landa-Silva, Professor D
Researcher Co-Investigators:
Project Partners:
Real Time Solutions Ltd
Department: School of Computer Science
Organisation: University of Nottingham
Scheme: Standard Research (Pre-FEC)
Starts: 08 April 2005 Ends: 07 October 2009 Value (£): 205,378
EPSRC Research Topic Classifications:
Artificial Intelligence Mathematical Aspects of OR
EPSRC Industrial Sector Classifications:
Construction Information Technologies
Related Grants:
Panel History:  
Summary on Grant Application Form
K. SummaryDescribe the proposed research using (about 200) words geared to the non-specialist reader.This ambitious project will attempt to exploit recent research advances in decision support technology which have opened up a range of exciting and ambitious research directions in the crucially important area of building space allocation and layout. This inter-disciplinary programme of research will draw upon the ASAP group's expertise across Operational Research and Artificial Intelligence to expand upon significant multi-objective advances that have been made by the investigators on a range of complex real world space allocation problems. It will also draw upon problem specific expertise from Real Time Solutions Ltd and the School of the Built Environment to ensure that the project tackles the problems and issues that are required in the commercial and real world environment. The project will attempt to integrate and develop ground breaking cutting/packing heuristics (which have been developed within the ASAP group) for such problems. These cutting/packing heuristics have generated the best published results on a wide range of standard benchmark problems and there are certain exploitable similarities with cutting/packing problems and the complex space allocation problems that will be addressed in this project. In addition, we will build upon recent advances in meta-heuristics for space allocation problems. Many successful optimisation methods have been developed by hybridising heuristic and meta-heuristic approaches with each other. We will rigorously explore the pros and cons of hybridising the developed approaches in a multi-objective context. In particular, we will explore the development of co-operative populations of multi-objective local search methods. Such approaches have already been shown to be successful for certain space allocation problems. The project will also build on advances by the ASAP group in adaptive heuristic technology. These adaptive heuristic methods can intelligently turn bad heuristics into good heuristics. We aim to investigate and develop such methods for multi-objective real world space allocation problems. The project team will work closely with Real Time Solutions Ltd who will supply a wide range of real world problem data sets, expertise and software. The project will interact
Key Findings
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Potential use in non-academic contexts
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Date Materialised
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Further Information:  
Organisation Website: http://www.nottingham.ac.uk