Nallaperuma, S., Neumann, F. and Sudholt, D. orcid.org/0000-0001-6020-1646 (2016) Expected Fitness Gains of Randomized Search Heuristics for the Traveling Salesperson Problem. Evolutionary Computation. ISSN 1063-6560
Abstract
Randomized search heuristics are frequently applied to NP-hard combinatorial optimization problems. The runtime analysis of randomized search heuristics has contributed tremendously to their theoretical understanding. Recently, randomized search heuristics have been examined regarding their achievable progress within a fixed time budget. We follow this approach and present a fixed budget analysis for an NP-hard combinatorial optimization problem. We consider the well-known Traveling Salesperson problem (TSP) and analyze the fitness increase that randomized search heuristics are able to achieve within a given fixed time budget. In particular, we analyze Manhattan and Euclidean TSP instances and Randomized Local Search (RLS), (1 + 1) EA and (1 + λ) EA algorithms for the TSP in a smoothed complexity setting and derive the lower bounds of the expected fitness gain for a specified number of generations.
Metadata
Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 by the Massachusetts Institute of Technology. Reproduced in accordance with the publisher's self-archiving policy. | ||||
Keywords: | Traveling Salesperson Problem; fitness gain; fixed-budget analysis; runtime analysis theory | ||||
Dates: |
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Institution: | The University of Sheffield | ||||
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) | ||||
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Depositing User: | Symplectic Sheffield | ||||
Date Deposited: | 19 Dec 2016 16:03 | ||||
Last Modified: | 28 Feb 2017 01:38 | ||||
Published Version: | http://dx.doi.org/10.1162/EVCO_a_00199 | ||||
Status: | Published | ||||
Publisher: | Massachusetts Institute of Technology Press (MIT Press): STM Titles | ||||
Refereed: | Yes | ||||
Identification Number: | https://doi.org/10.1162/EVCO_a_00199 | ||||
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