Dr Sarah L. Thomson S.Thomson4@napier.ac.uk
Lecturer
In this paper a multi-drug Chemotherapy Schedule Optimisation Problem (CSOP) is subject to Local Optima Network (LON) analysis. LONs capture global patterns in fitness landscapes. CSOPs have not previously been subject to fitness landscape analysis. We fill this gap: LONs are constructed and studied for meaningful structure. The CSOP formulation presents novel challenges and questions for the LON model because there are infeasible regions in the fitness landscape and an unknown global optimum; it also brings a topic from healthcare to LON analysis. Two LON Construction algorithms are proposed for sampling CSOP fitness landscapes: a Markov-Chain Construction Algorithm and a Hybrid Construction Algorithm. The results provide new insight into LONs of highly-constrained spaces, and into the proficiency of search operators on the CSOP. Iterated Local Search and Memetic Search, which are the foundations for the LON algorithms, are found to markedly out-perform a Genetic Algorithm from the literature.
Thomson, S. L., & Ochoa, G. (2020, April). The Local Optima Level in Chemotherapy Schedule Optimisation. Presented at EvoCOP 2020: Evolutionary Computation in Combinatorial Optimization, Seville, Spain
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | EvoCOP 2020: Evolutionary Computation in Combinatorial Optimization |
Start Date | Apr 15, 2020 |
End Date | Apr 17, 2020 |
Online Publication Date | Apr 9, 2020 |
Publication Date | 2020 |
Deposit Date | Aug 16, 2023 |
Publisher | Springer |
Pages | 197-213 |
Series Title | Lecture Notes in Computer Science |
Series Number | 12102 |
Book Title | Evolutionary Computation in Combinatorial Optimization: 20th European Conference, EvoCOP 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings |
ISBN | 9783030436797 |
DOI | https://doi.org/10.1007/978-3-030-43680-3_13 |
Keywords | Combinatorial fitness landscapes, Local Optima Networks, Search space analysis |
Public URL | http://researchrepository.napier.ac.uk/Output/3169648 |
The Easiest Hard Problem: Now Even Easier
(2024)
Presentation / Conference Contribution
Channel Configuration for Neural Architecture: Insights from the Search Space
(2023)
Presentation / Conference Contribution
From Fitness Landscapes to Explainable AI and Back
(2023)
Presentation / Conference Contribution
Randomness in Local Optima Network Sampling
(2023)
Presentation / Conference Contribution
Universally Hard Hamiltonian Cycle Problem Instances
(2022)
Presentation / Conference Contribution
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
Apache License Version 2.0 (http://www.apache.org/licenses/)
Apache License Version 2.0 (http://www.apache.org/licenses/)
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search