Results 81 to 90 of about 786,097 (340)
Epigenetic opportunities for Evolutionary Computation [PDF]
Evolutionary Computation is a group of biologically inspired algorithms used to solve complex optimisation problems. It can be split into Evolutionary Algorithms, which take inspiration from genetic inheritance, and Swarm Intelligence algorithms, that take inspiration from cultural inheritance. However, recent developments have focused on computational
arxiv
Stability of evolutionary algorithms
AbstractWe prove under mild conditions the convergence of some evolutionary algorithm to the solution of the global optimization problem. In the proof, the Lyapunov function's techniques is applied to some semi-dynamical system generated by a Foias operator on the space of the probability measures defined on the set of admissible solutions.
openaire +3 more sources
Understanding and measuring mechanical signals in the tumor stroma
This review discusses cancerâassociated fibroblast subtypes and their functions, particularly in relation to extracellular matrix production, as well as the development of 3D models to study tumor stroma mechanics in vitro. Several quantitative techniques to measure tissue mechanical properties are also described, to emphasize the diagnostic and ...
FĂ tima de la Jara Ortiz+3 more
wiley +1 more source
Developing metaheuristic algorithms has been paid more recent attention from researchers and scholars to address the optimization problems in many fields of studies.
Nengxian Liu+3 more
doaj +1 more source
An Analytic Expression of Relative Approximation Error for a Class of Evolutionary Algorithms [PDF]
An important question in evolutionary computation is how good solutions evolutionary algorithms can produce. This paper aims to provide an analytic analysis of solution quality in terms of the relative approximation error, which is defined by the error between 1 and the approximation ratio of the solution found by an evolutionary algorithm.
arxiv +1 more source
This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi+2 more
wiley +1 more source
Runtime Analysis of Competitive co-Evolutionary Algorithms for Maximin Optimisation of a Bilinear Function [PDF]
Co-evolutionary algorithms have a wide range of applications, such as in hardware design, evolution of strategies for board games, and patching software bugs. However, these algorithms are poorly understood and applications are often limited by pathological behaviour, such as loss of gradient, relative over-generalisation, and mediocre objective stasis.
arxiv
Tree Contractions and Evolutionary Trees [PDF]
An evolutionary tree is a rooted tree where each internal vertex has at least two children and where the leaves are labeled with distinct symbols representing species. Evolutionary trees are useful for modeling the evolutionary history of species.
Kao, Ming-Yang
core
On the Analysis of Evolutionary Algorithms [PDF]
There is a lot of experimental evidence that crossover is, for some functions, an essential operator of evolutionary algorithms. Nevertheless, it was an open problem to prove for some function that an evolutionary algorithm using crossover is essentially more efficient than evolutionary algorithms without crossover.
Jansen, Thomas, Wegener, Ingo
openaire +2 more sources
In modern times, swarm intelligence has played an increasingly important role in finding an optimal solution within a search range. This study comes up with a novel solution algorithm named QUasi-Affine TRansformation-Pigeon-Inspired Optimization ...
Xiao-Xue Sun+4 more
doaj +1 more source