208 related articles for article (PubMed ID: 29446983)
1. Multi-Objectivising Combinatorial Optimisation Problems by Means of Elementary Landscape Decompositions.
Ceberio J; Calvo B; Mendiburu A; Lozano JA
Evol Comput; 2019; 27(2):291-311. PubMed ID: 29446983
[TBL] [Abstract][Full Text] [Related]
2. Landscape Analysis of a Class of NP-Hard Binary Packing Problems.
Alyahya K; Rowe JE
Evol Comput; 2019; 27(1):47-73. PubMed ID: 30365387
[TBL] [Abstract][Full Text] [Related]
3. Automatic Configuration of Multi-Objective Local Search Algorithms for Permutation Problems.
Blot A; Kessaci MÉ; Jourdan L; Hoos HH
Evol Comput; 2019; 27(1):147-171. PubMed ID: 30407875
[TBL] [Abstract][Full Text] [Related]
4. Problem Features versus Algorithm Performance on Rugged Multiobjective Combinatorial Fitness Landscapes.
Daolio F; Liefooghe A; Verel S; Aguirre H; Tanaka K
Evol Comput; 2017; 25(4):555-585. PubMed ID: 27689467
[TBL] [Abstract][Full Text] [Related]
5. A methodology to find the elementary landscape decomposition of combinatorial optimization problems.
Chicano F; Whitley LD; Alba E
Evol Comput; 2011; 19(4):597-637. PubMed ID: 21469972
[TBL] [Abstract][Full Text] [Related]
6. Metaheuristic Optimisation Algorithms for Tuning a Bioinspired Retinal Model.
Crespo-Cano R; Cuenca-Asensi S; Fernández E; Martínez-Álvarez A
Sensors (Basel); 2019 Nov; 19(22):. PubMed ID: 31698827
[TBL] [Abstract][Full Text] [Related]
7. Constraint Handling Guided by Landscape Analysis in Combinatorial and Continuous Search Spaces.
Malan KM; Moser I
Evol Comput; 2019; 27(2):267-289. PubMed ID: 29528726
[TBL] [Abstract][Full Text] [Related]
8. Inferring Future Landscapes: Sampling the Local Optima Level.
Thomson SL; Ochoa G; Verel S; Veerapen N
Evol Comput; 2020; 28(4):621-641. PubMed ID: 32101026
[TBL] [Abstract][Full Text] [Related]
9. Evolutionary and Estimation of Distribution Algorithms for Unconstrained, Constrained, and Multiobjective Noisy Combinatorial Optimisation Problems.
Aishwaryaprajna ; Rowe JE
Evol Comput; 2023 Sep; 31(3):259-285. PubMed ID: 36854020
[TBL] [Abstract][Full Text] [Related]
10. Identifying Features of Fitness Landscapes and Relating Them to Problem Difficulty.
Moser I; Gheorghita M; Aleti A
Evol Comput; 2017; 25(3):407-437. PubMed ID: 26928851
[TBL] [Abstract][Full Text] [Related]
11. A lifelong learning hyper-heuristic method for bin packing.
Sim K; Hart E; Paechter B
Evol Comput; 2015; 23(1):37-67. PubMed ID: 24512321
[TBL] [Abstract][Full Text] [Related]
12. Theoretical Analysis of Local Search and Simple Evolutionary Algorithms for the Generalized Travelling Salesperson Problem.
Pourhassan M; Neumann F
Evol Comput; 2019; 27(3):525-558. PubMed ID: 29932364
[TBL] [Abstract][Full Text] [Related]
13. Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.
Moreno-Scott JH; Ortiz-Bayliss JC; Terashima-Marín H; Conant-Pablos SE
Comput Intell Neurosci; 2016; 2016():7349070. PubMed ID: 26949383
[TBL] [Abstract][Full Text] [Related]
14. Decomposition Algorithms for a Multi-Hard Problem.
Przybylek MR; Wierzbicki A; Michalewicz Z
Evol Comput; 2018; 26(3):507-533. PubMed ID: 28632397
[TBL] [Abstract][Full Text] [Related]
15. Objective space division-based hybrid evolutionary algorithm for handing overlapping solutions in combinatorial problems.
González B; Rossit DA; Méndez M; Frutos M
Math Biosci Eng; 2022 Jan; 19(4):3369-3401. PubMed ID: 35341256
[TBL] [Abstract][Full Text] [Related]
16. Comparing evolutionary strategies on a biobjective cultural algorithm.
Lagos C; Crawford B; Cabrera E; Soto R; Rubio JM; Paredes F
ScientificWorldJournal; 2014; 2014():745921. PubMed ID: 25254257
[TBL] [Abstract][Full Text] [Related]
17. Simple Hyper-Heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes
Lissovoi A; Oliveto PS; Warwicker JA
Evol Comput; 2020; 28(3):437-461. PubMed ID: 31120773
[TBL] [Abstract][Full Text] [Related]
18. Automated Algorithm Selection: Survey and Perspectives.
Kerschke P; Hoos HH; Neumann F; Trautmann H
Evol Comput; 2019; 27(1):3-45. PubMed ID: 30475672
[TBL] [Abstract][Full Text] [Related]
19. Strength Pareto particle swarm optimization and hybrid EA-PSO for multi-objective optimization.
Elhossini A; Areibi S; Dony R
Evol Comput; 2010; 18(1):127-56. PubMed ID: 20064026
[TBL] [Abstract][Full Text] [Related]
20. Graph-based molecular Pareto optimisation.
Verhellen J
Chem Sci; 2022 Jun; 13(25):7526-7535. PubMed ID: 35872811
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]