Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/24819
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Peer Review Status: Refereed
Authors: Ochoa, Gabriela
Veerapen, Nadarajen
Daolio, Fabio
Tomassini, Marco
Contact Email: nve@cs.stir.ac.uk
Title: Understanding Phase Transitions with Local Optima Networks: Number Partitioning as a Case Study
Editors: Bin, H
Lopez-Ibanez, M
Citation: Ochoa G, Veerapen N, Daolio F & Tomassini M (2017) Understanding Phase Transitions with Local Optima Networks: Number Partitioning as a Case Study In: Bin H, Lopez-Ibanez M (ed.) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2017, Cham, Switzerland: Springer. 17th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP), 19.4.2017 - 21.4.2017, Amsterdam, The Netherlands.
Issue Date: 9-Mar-2017
Series/Report no.: Lecture Notes in Computer Science, 10197
Conference Name: 17th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP)
Conference Dates: 2017-04-19T00:00:00Z
Conference Location: Amsterdam, The Netherlands
Abstract: Phase transitions play an important role in understanding search difficulty in combinatorial optimisation. However, previous attempts have not revealed a clear link between fitness landscape properties and the phase transition. We explore whether the global landscape structure of the number partitioning problem changes with the phase transition. Using the local optima network model, we analyse a number of instances before, during, and after the phase transition. We compute relevant network and neutrality metrics; and importantly, identify and visualise the funnel structure with an approach ( monotonic sequences) inspired by theoretical chemistry. While most metrics remain oblivious to the phase transition, our results reveal that the funnel structure clearly changes. Easy instances feature a single or a small number of dominant funnels leading to global optima; hard instances have a large number of suboptimal funnels attracting the search. Our study brings new insights and tools to the study of phase transitions in combinatorial optimisation.
Status: Book Chapter: author post-print (pre-copy editing)
Rights: Publisher policy allows this work to be made available in this repository. Published in Hu B., López-Ibáñez M. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2017. Lecture Notes in Computer Science, vol 10197; The final publication is available at Springer via https://doi.org/10.1007/978-3-319-55453-2_16
URL: https://link.springer.com/chapter/10.1007/978-3-319-55453-2_16

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