Results 31 to 40 of about 715,075 (267)
, 2018 Theoretical and empirical research on evolutionary computation methods complement each other by providing two fundamentally different approaches towards a better understanding of black-box optimization heuristics.
Badkobeh Golnaz +5 more
core +1 more source
Energy Minimization of Discrete Protein Titration State Models Using Graph Theory
, 2016 There are several applications in computational biophysics which require the optimization of discrete interacting states; e.g., amino acid titration states, ligand oxidation states, or discrete rotamer angles. Such optimization can be very time-consuming
Baker, Nathan A. +4 more
core +2 more sources
Continuous Optimization of Adaptive Quadtree Structures
, 2018 We present a novel continuous optimization method to the discrete problem of quadtree optimization. The optimization aims at achieving a quadtree structure with the highest mechanical stiffness, where the edges in the quadtree are interpreted as ...
Wu, Jun
core +1 more source
The backtracking survey propagation algorithm for solving random K-SAT problems [PDF]
, 2016 Discrete combinatorial optimization has a central role in many scientific disciplines, however, for hard problems we lack linear time algorithms that would allow us to solve very large instances.
Marino, Raffaele +2 more
core +2 more sources
Integrated optimization of timetabling and Electric Vehicle Scheduling
EURO Journal on Transportation and LogisticsWe tackle the integrated planning problem of periodic timetabling and electric vehicle scheduling, crucial for cities transitioning to electric bus fleets.
Vladimir Stadnichuk +3 more
doaj +1 more source
An Optimized Discrete Dragonfly Algorithm Tackling the Low Exploitation Problem for Solving TSP
Mathematics, 2022 Optimization problems are prevalent in almost all areas and hence optimization algorithms are crucial for a myriad of real-world applications. Deterministic optimization algorithms tend to be computationally costly and time-consuming.
Bibi Aamirah Shafaa Emambocus +3 more
doaj +1 more source
The Discrete Dantzig Selector: Estimating Sparse Linear Models via Mixed Integer Linear Optimization
, 2017 We propose a novel high-dimensional linear regression estimator: the Discrete Dantzig Selector, which minimizes the number of nonzero regression coefficients subject to a budget on the maximal absolute correlation between the features and residuals ...
Mazumder, Rahul, Radchenko, Peter
core +1 more source
Molecular Oncology, EarlyView.To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley +1 more source
FEBS Open Bio, EarlyView.KLK7, a tissue kallikrein‐related peptidase, is elevated in advanced colorectal cancer and associated with shorter survival. High KLK7 levels in ascites correlate with peritoneal metastasis. In mice, KLK7 overexpression increases metastasis. In vitro, KLK7 enhances cancer cell proliferation, migration, adhesion, and spheroid formation, driving ...
Yosr Z. Haffani +6 more
wiley +1 more source
Evolutionary multi-stage financial scenario tree generation
, 2010 Multi-stage financial decision optimization under uncertainty depends on a careful numerical approximation of the underlying stochastic process, which describes the future returns of the selected assets or asset categories.
A. Brabazon +16 more
core +1 more source