Results 51 to 60 of about 5,817,365 (365)

Noisy Optimization: Convergence with a Fixed Number of Resamplings [PDF]

, 2014
It is known that evolution strategies in continuous domains might not converge in the presence of noise. It is also known that, under mild assumptions, and using an increasing number of resamplings, one can mitigate the effect of additive noise and ...
A Auger, D Arnold, DV Arnold, H Chen, H-G Beyer, I Rechenberg, O Teytaud, R Coulom, V Fabian   +8 more
core   +3 more sources

A New DG Multiobjective Optimization Method Based on an Improved Evolutionary Algorithm

Journal of Applied Mathematics, 2013
A distribution generation (DG) multiobjective optimization method based on an improved Pareto evolutionary algorithm is investigated in this paper. The improved Pareto evolutionary algorithm, which introduces a penalty factor in the objective function ...
Wanxing Sheng, Ke-yan Liu, Yongmei Liu, Xiaoli Meng, Xiaohui Song   +4 more
doaj   +1 more source

Clinical applications of next‐generation sequencing‐based ctDNA analyses in breast cancer: defining treatment targets and dynamic changes during disease progression

Molecular Oncology, EarlyView.
Circulating tumor DNA (ctDNA) offers a possibility for different applications in early and late stage breast cancer management. In early breast cancer tumor informed approaches are increasingly used for detecting molecular residual disease (MRD) and early recurrence. In advanced stage, ctDNA provides a possibility for monitoring disease progression and
Eva Valentina Klocker, Samantha Hasenleithner, Rupert Bartsch, Simon P. Gampenrieder, Daniel Egle, Christian F. Singer, Gabriel Rinnerthaler, Michael Hubalek, Katja Schmitz, Zsuzsanna Bago‐Horvath, Andreas Petzer, Sonja Heibl, Ellen Heitzer, Marija Balic, Michael Gnant   +14 more
wiley   +1 more source

An Investigation Into the use of Swarm Intelligence for an Evolutionary Algorithm Optimisation; The Optimisation Performance of Differential Evolution Algorithm Coupled with Stochastic Diffusion Search [PDF]

, 2011
The integration of Swarm Intelligence (SI) algorithms and Evolutionary algorithms (EAs) might be one of the future approaches in the Evolutionary Computation (EC).
al-Rifaie, Mohammad Majid, Bishop, Mark (J. M.), Blackwell, Tim M.   +2 more
core  

A New Dominance Relation-Based Evolutionary Algorithm for Many-Objective Optimization

IEEE Transactions on Evolutionary Computation, 2016
Many-objective optimization has posed a great challenge to the classical Pareto dominance-based multiobjective evolutionary algorithms (MOEAs). In this paper, an evolutionary algorithm based on a new dominance relation is proposed for many-objective ...
Yuan Yuan, Hua Xu, Bo D. Wang, X. Yao
semanticscholar   +1 more source

Emergence of Novelty in Evolutionary Algorithms

The 2022 Conference on Artificial Life, 2022
One of the main problems of evolutionary algorithms is the convergence of the population to local minima. In this paper, we explore techniques that can avoid this problem by encouraging a diverse behavior of the agents through a shared reward system.
Herel, David, Zogatova, Dominika, Kripner, Matej, Mikolov, Tomas   +3 more
openaire   +2 more sources

Circulating tumor DNA (ctDNA) trajectories predict survival in trifluridine/tipiracil‐treated metastatic colorectal cancer patients

Molecular Oncology, EarlyView.
The authors applied joint/mixed models that predict mortality of trifluridine/tipiracil‐treated metastatic colorectal cancer patients based on circulating tumor DNA (ctDNA) trajectories. Patients at high risk of death could be spared aggressive therapy with the prospect of a higher quality of life in their remaining lifetime, whereas patients with a ...
Matthias Unseld, Stefan Kühberger, Ricarda Graf, Christine Beichler, Markus Braun, Nadia Dandachi, Ellen Heitzer, Gerald W. Prager   +7 more
wiley   +1 more source

Combination of Evolutionary Algorithms with Experimental Design, Traditional Optimization and Machine Learning [PDF]

, 2016
Evolutionary algorithms alone cannot solve optimization problems very efficiently since there are many random (not very rational) decisions in these algorithms.
Zhang, Qingfu
core  

Evolutionary Algorithms for the Satisfiability Problem [PDF]

Evolutionary Computation, 2002
Several evolutionary algorithms have been proposed for the satisfiability problem. We review the solution representations suggested in literature and choose the most promising one the bit string representation for further evaluation. An empirical comparison on commonly used benchmarks is presented for the most successful evolutionary algorithms and ...
Jens Gottlieb, Elena Marchiori, Claudio Rossi   +2 more
openaire   +4 more sources

Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma

Molecular Oncology, EarlyView.
This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu, Jianchao Wang, Fuqing Chen, Xuefeng Wang, Bin Lan, Ruyi Fu, Hong Wen, Fangfang Chen, Wei Hong, Tian‐Yu Tang, Ying He, Gang Chen, Jianyin Zhou, Hai‐Long Piao, Di Chen, Shu‐Yong Lin   +15 more
wiley   +1 more source