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Publication search results
found 47 matches
- 2024
- Kevin G. Lohan, Zachary R. Putnam:
Characterization of Candidate Solutions for X-Ray Pulsar Navigation. IEEE Trans. Aerosp. Electron. Syst. 60(3): 2749-2762 (2024) - Salih Berkan Aydemir:
Ideal solution candidate search for starling murmuration optimizer and its applications on global optimization and engineering problems. J. Supercomput. 80(3): 4083-4156 (2024) - Nagadivya Balasubramaniam, Marjo Kauppinen, Hong Linh Truong, Sari Kujala:
Candidate Solutions for Defining Explainability Requirements of AI Systems. REFSQ 2024: 129-146 - 2023
- Flávio Rosendo Da Silva Oliveira, Fernando Buarque de Lima Neto:
Method to Produce More Reasonable Candidate Solutions With Explanations in Intelligent Decision Support Systems. IEEE Access 11: 20861-20876 (2023) - Cristiano Maciel da Silva, João Fernando Machry Sarubbi, Somayeh Mokhtari, Leonardo Alvarenga L. Santos, Lucas Diniz Silva, Fernanda Sumika Hojo de Souza, Daniel Ludovico Guidoni, José Marcos Silva Nogueira:
RAGE: A novel strategy for solving non-polynomial problems through the random generation of solutions and incremental reduction of the number of candidates: A case study applied to the design of the network infrastructure for connected vehicles. Expert Syst. Appl. 213(Part): 118900 (2023) - Akihiro Fujii, Hideki Tsunashima, Yoshihiro Fukuhara, Koji Shimizu, Satoshi Watanabe:
Enhancing Inverse Problem Solutions with Accurate Surrogate Simulators and Promising Candidates. CoRR abs/2304.13860 (2023) - 2022
- Malte Chlosta, Jianlei Liu, Rafael Poppenborg, Richard Lutz, Kevin Förderer, Thorsten Schlachter, Veit Hagenmeyer:
An adapter-based architecture for evaluating candidate solutions in energy system scheduling. Energy Inform. 5 (2022) - Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Fast Greedy Subset Selection From Large Candidate Solution Sets in Evolutionary Multiobjective Optimization. IEEE Trans. Evol. Comput. 26(4): 750-764 (2022) - Ke Shang, Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang:
Benchmarking Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization. CoRR abs/2201.06700 (2022) - 2021
- Jianli Cao, Zhikui Chen, Yuxin Wang, He Guo:
Parallel Implementations of Candidate Solution Evaluation Algorithm for N-Queens Problem. Complex. 2021: 6694944:1-6694944:15 (2021) - Konstantinos Liagkouras, Konstantinos Metaxiotis:
Improving multi-objective algorithms performance by emulating behaviors from the human social analogue in candidate solutions. Eur. J. Oper. Res. 292(3): 1019-1036 (2021) - Mariusz Oszust, Grzegorz Sroka, Karol Cymerys:
A hybridization approach with predicted solution candidates for improving population-based optimization algorithms. Inf. Sci. 574: 133-161 (2021) - Sikun Xu, Ruoyi Ma, Daniel K. Molzahn, Hassan L. Hijazi, Cédric Josz:
Verifying Global Optimality of Candidate Solutions to Polynomial Optimization Problems using a Determinant Relaxation Hierarchy. CDC 2021: 3143-3148 - Zhenzhong Gao, Masahiro Inuiguchi:
Estimating the Optimal Probability of a Candidate Basic Solution in Stochastic Linear Programming. SICE 2021: 640-643 - Ilya Jackson, Josue C. Velazquez-Martinez:
Automl Approach to Classification of Candidate Solutions for Simulation Models of Logistic Systems. WSC 2021: 1-12 - Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Fast Greedy Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization. CoRR abs/2102.00941 (2021) - 2020
- Abdulkerim Mohammed Yibre:
Development of a novel candidate solution quality prediction approach to artificial algae algorithm (Yapay alg algoritması için yeni bir aday çözüm kalite tahmin yaklaşımı geliştirilmesi). Selçuk University, Turkey, 2020 - Abdulkerim Mohammed Yibre, Baris Koçer:
Improving artificial algae algorithm performance by predicting candidate solution quality. Expert Syst. Appl. 150: 113298 (2020) - Algirdas Lancinskas, Julius Zilinskas, Pascual Fernández, Blas Pelegrín:
Solution of asymmetric discrete competitive facility location problems using ranking of candidate locations. Soft Comput. 24(23): 17705-17713 (2020) - Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Lazy Greedy Hypervolume Subset Selection from Large Candidate Solution Sets. CEC 2020: 1-8 - Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Lazy Greedy Hypervolume Subset Selection from Large Candidate Solution Sets. CoRR abs/2007.02050 (2020) - Julian D. Schiller, Sven Knüfer, Matthias A. Müller:
Robust Stability of Suboptimal Moving Horizon Estimation using an Observer-Based Candidate Solution. CoRR abs/2011.08723 (2020) - 2019
- Hazim Iscan, Mustafa Servet Kiran, Mesut Gündüz:
A Novel Candidate Solution Generation Strategy for Fruit Fly Optimizer. IEEE Access 7: 130903-130921 (2019) - Masaya Sakakibara, Akira Notsu, Seiki Ubukata, Katsuhiro Honda:
Designation of Candidate Solutions in Differential Evolution Based on Bandit Algorithm and its Evaluation. J. Adv. Comput. Intell. Intell. Informatics 23(4): 758-766 (2019) - Sahibzada Muhammad Shuja, Nadeem Javaid, Muhammad Zeeshan Rafique, Umar Qasim, Raja Farhat Makhdoom Khan, Ayesha Anjum Butt, Murtaza Hanif:
Towards Efficient Scheduling of Smart Appliances for Energy Management by Candidate Solution Updation Algorithm in Smart Grid. AINA 2019: 67-81 - 2018
- Iker Beñaran-Muñoz, Jerónimo Hernández-González, Aritz Pérez:
Crowd Learning with Candidate Labeling: An EM-Based Solution. CAEPIA 2018: 13-23 - Zhao Chen, Peng Cheng, Chen Zhang, Lei Chen:
Effective Solution for Labeling Candidates with a Proper Ration for Efficient Crowdsourcing. DASFAA (2) 2018: 386-394 - Lorenzo Perino, Akihiro Fujii, Tsuyoshi Waku, Akira Kobayashi, Satoru Hiwa, Tomoyuki Hiroyasu:
Solution exploration using multi-objective genetic algorithm for determining experiment candidate. GECCO (Companion) 2018: 1584-1589 - Akira Notsu, Masaya Sakakibara, Seiki Ubukata, Katsuhiro Honda:
Setting of Candidate Solutions Considering Confidence Intervals in Differential Evolution. iFUZZY 2018: 7-11 - 2017
- Junfeng Chen, Yingjuan Xie, Hua Chen, Qiwen Yang, Shi Cheng, Yuhui Shi:
An improved extremal optimization based on the distribution knowledge of candidate solutions. Nat. Comput. 16(1): 135-149 (2017)
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