20 papers · ranked by Valyu relevance
C. Feng, Minyang Chen, Zhuozhao Li, Ran Cheng
—Since Differential Evolution (DE) is sensitive to strategy choice, most existing variants pursue performance through adaptive mechanisms or intricate designs. While these approaches focus on adjusting strategies over time, the structural benefits that static strategy diversity may bring remain largely unexplored. To…
Tomofumi Kitamura, Alex Fukunaga
In single-objective optimization, multiple continuous-valued variables are optimized to minimize a single objective function. A single-objective optimization problem aims to find a real-valued vector x = (x1, · · · , xD), where D is the dimensionality of the problem, that minimizes an objective function f : R D → R.…
Shatendra Singh, Aruna Tiwari
Most of the real-world problems are multimodal in nature that consists of multiple optimum values. Multimodal optimization is defined as the process of finding multiple global and local optima (as opposed to a single solution) of a function. It enables a user to switch between different solutions as per the need while…
Kaijun Wu, Zhengnan Liu, Ning Ma, Dicong Wang
This study proposed a dynamic adaptive weighted differential evolution (DAWDE) algorithm to solve the problems of differential evolution (DE) algorithm such as long search time, easy stagnation, and local optimal solution. First, adaptive adjustment strategies of scaling factor and crossover factor are proposed, which…
Vladimir Stanovov, Sergey Khodenkov, Sergey Gorbunov, Ivan Rozhnov + 3 more
'Lev Kazakovtsev' 'Mohd Najib Mohd Yasin' 'Salam Khamas'] The microstrip devices based on multimode resonators represent a class of electromagnetic microwave devices, promising use in tropospheric communication, radar, and navigation systems. The design of wideband bandpass filters, diplexers, and multiplexers with…
Pawan Mishra, Musrrat Ali, Pooja, Safiqul Islam + 1 more
Differential evolution (DE) stands out as a prominent algorithm for addressing global optimization challenges. The efficacy of DE hinges crucially upon its mutation operation, which serves as a pivotal mechanism in generating diverse and high-quality solutions. This article explores various mutation operations aimed at…
Yuanqing Zhang, Baolin Xiong, Le Feng, Liang Li + 4 more
Quadrupole mass spectrometers are highly sensitive and specific analytical instruments, widely used in pharmaceuticals, clinical diagnostics, and other fields. Their performance depends on a tuning process to optimize key parameters, which has traditionally relied on engineers’ expertise or simple univariate search…
Dylan M. Janssen, Wayne Pullan, Alan Wee‐Chung Liew
Differential Evolution (DE) is a highly successful population based global optimisation algorithm, commonly used for solving numerical optimisation problems. However, as the complexity of the objective function increases, the wall-clock run-time of the algorithm suffers as many fitness function evaluations must take…
Mojtaba Ghasemi, Mohsen Zare, Pavel Trojovský, Amir Zahedibialvaei + 2 more
'Eva Trojovská' 'Bilal Alatas'] Differential evolution (DE) belongs to the most usable optimization algorithms, presented in many improved and modern versions in recent years. Generally, the low convergence rate is the main drawback of the DE algorithm. In this article, the gray wolf optimizer (GWO) is used to…
Jan A. Stampfli, Donald G. Olsen, Beat Wellig, René Hofmann
Title: Graphical abstract
Dikshit Chauhan, Anupam Trivedi, Shivani
Mechanisms for Single-objective Optimization Authors: ['Dikshit Chauhan' 'Anupam Trivedi' 'Shivani'] Abstract—In recent years, multi-operator and multi-method algorithms have succeeded, encouraging their combination within single frameworks. Despite promising results, there remains room for improvement as only some…
Daniel Gaissmaier, Matthias van den Borg, Donato Fantauzzi, Timo Jacob
In this work, we demonstrate the superior exploration capabilities of the population-based methods over the sequential one-parameter parabolic interpolation (SOPPI) approach to optimise ReaxFF force field parameters. Evolutionary algorithms (EAs) are heuristic-based approaches using a population of concurrent models in…
Diederick Vermetten, Fabio Caraffini, Anna V. Kononova, Thomas Bäck
New contributions in the field of iterative optimisation heuristics are often made in an iterative manner. Novel algorithmic ideas are not proposed in isolation, but usually as an extension of a preexisting algorithm. Although these contributions are often compared to the base algorithm, it is challenging to make fair…
Husanbir Singh Pannu, Douglas B. Kell
We analyse the effectiveness of differential evolution hyperparameters in large-scale search problems, i.e. those with very many variables or vector elements, using a novel objective function that is easily calculated from the vector/string itself. The objective function is simply the sum of the differences between…
Khushi Goda, Fikret Isik
A newly developed software, AgMate, was used to perform optimized mating for monoecious Pinus taeda L. breeding. Using a computational optimization procedure called differential evolution (DE), AgMate was applied under different breeding population sizes scenarios (50, 100, 150, 200, 250) and candidate contribution…
Sebastian Towers, Jessica James, Harrison Steel, Idris Kempf
Directed evolution is a method for engineering biological systems or components, such as proteins, wherein desired traits are optimised through iterative rounds of mutagenesis and selection of fit variants. The process of protein directed evolution can be envisaged as navigation over high-dimensional landscapes with…
Alexander Lalejini, Emily Dolson, Anya E. Vostinar, Luis Zaman
Directed microbial evolution harnesses evolutionary processes in the laboratory to construct microorganisms with enhanced or novel functional traits. Attempting to direct evolutionary processes for applied goals is fundamental to evolutionary computation, which harnesses the principles of Darwinian evolution as a…
Mauricio González-Forero
Mathematically integrating genetics, development, and evolution is a longstanding challenge. Here I develop general mathematical theory that integrates sexual, discrete, multilocus genetics, development, and evolution. This yields an exact method to describe the evolutionary dynamics of allele frequencies and linkage…
Andre KY Low, Flore Mekki-Berrada, Aleksandr Ostudin, Jiaxun Xie + 7 more
The development of automated high-throughput experimental platforms has enabled fast sampling of high-dimensional decision spaces. To reach target properties efficiently, these platforms are increasingly paired with intelligent experimental design. When solving optimization problems, Bayesian-based optimizers are often…
Amit Kahana, Lior Segev, Doron Lancet
The origin of life must have involved an unlikely transition from chaotic chemistry to reproducing supramolecular structures. Previous quantitative analyses of reproducing mutually catalytic networks made of simple molecules have led to increasing popularity of this pre-RNA scenario for life’s origin. Here, we…