25 papers · ranked by Valyu relevance
Mohd Nadhir Ab Wahab, Samia Nefti-Meziani, Adham Atyabi, Catalin Buiu
'Catalin Buiu'] Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known…
Anna V. Kononova, Fabio Caraffini, Thomas Bäck
This paper investigates how often the popular configurations of Differential Evolution generate solutions outside the feasible domain. Following previous publications in the field, we argue that what the algorithm does with such solutions and how often this has to happen is important for the overall performance of the…
Xin‐She Yang, Suash Deb
Efficiency of an optimization process is largely determined by the search algorithm and its fundamental characteristics. In a given optimization, a single type of algorithm is used in most applications. In this paper, we will investigate the Eagle Strategy recently developed for global optimization, which uses a…
Sandeep Kumar, Vivek Sharma, Rajani Kumari
Differential Evolution (DE) is a renowned optimization stratagem that can easily solve nonlinear and comprehensive problems. DE is a well known and uncomplicated population based probabilistic approach for comprehensive optimization. It has apparently outperformed a number of Evolutionary Algorithms and further search…
Zhaolu Guo, Haixia Huang, Changshou Deng, Xuezhi Yue + 1 more
Differential evolution (DE) is a simple yet efficient evolutionary algorithm for real-world engineering problems. However, its search ability should be further enhanced to obtain better solutions when DE is applied to solve complex optimization problems. This paper presents an enhanced differential evolution with elite…
Wan-li Xiang, Xue-lei Meng, Mei-qing An, Yin-zhen Li + 1 more
Differential evolution algorithm is a simple yet efficient metaheuristic for global optimization over continuous spaces. However, there is a shortcoming of premature convergence in standard DE, especially in DE/best/1/bin. In order to take advantage of direction guidance information of the best individual of…
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…
Necmettin Kaya
The objective of this study is to design rubber bushing at desired level of stiffness characteristics in order to achieve the ride quality of the vehicle. A differential evolution algorithm based approach is developed to optimize the rubber bushing through integrating a finite element code running in batch mode to…
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…
Konstantin Kozlov, Dmitry Chebotarov, Mehedi Hassan, Martin Triska + 3 more
The genetic structure of human populations is extraordinarily complex and of fundamental importance to studies of anthropology, evolution, and medicine. As increasingly many individuals are of mixed origin, there is an unmet need for tools that can infer multiple origins. Misclassification of such individuals can lead…
Haiming Du, Zaichao Wang, Yiqun Fan, Chengjun Li + 2 more
'Alberto Fernández-Hilario'] Differential Evolution (DE) is powerful for global optimization problems. Among DE algorithms, JADE and its variants, whose mutation strategy is DE/current-to-pbest/1 with optional archive, have good performance. A significant feature of the above mutation strategy is that one individual…
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…
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.…
Mona Nasr, Omar Farouk, Ahmed Mohamedeen, Ali Elrafie + 2 more
'Marwan Bedeir' 'Ali Khaled'] Solving an optimization task in any domain is a very challenging problem, especially when dealing with nonlinear problems and non-convex functions. Many meta-heuristic algorithms are very efficient when solving nonlinear functions. A meta-heuristic algorithm is a problem-independent…
Hossein Sharifi-Noghabi, Habib Rajabi Mashhadi, Kambiz Shojaee
Differential Evolution (DE) is one of the most successful and powerful evolutionary algorithms for global optimization problem. The most important operator in this algorithm is mutation operator which parents are selected randomly to participate in it. Recently, numerous papers are tried to make this operator more…
Muhammad Farman, Muhammad Farhan Tabassum, Muhammad Saeed, Nazir Ahmad Chaudhry
Hepatitis B is the main public health problem of the whole world. In epidemiology, mathematical models perform a key role in understanding the dynamics of infectious diseases. This paper proposes Padé approximation (Pa) with Differential Evolution (DE) for obtaining solution of Hepatitis-B model which is nonlinear…
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…
Jakub M. Tomczak, Ewelina Węglarz‐Tomczak, A. E. Eiben
Differential evolution (DE) is a well-known type of evolutionary algorithms (EA). Similarly to other EA variants it can suffer from small populations and loose diversity too quickly. This paper presents a new approach to mitigate this issue: We propose to generate new candidate solutions by utilizing reversible linear…
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…
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…
Szabolcs Számadó, Dustin J. Penn
The relationship between signal cost and honesty is a controversial and unresolved issue. The handicap principle assumes that signals must be costly at equilibrium to be honest, and the greater the cost, the more reliable the signal. However, theoretical models and simulations question the necessity of equilibrium cost…
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…
Authors not listed
Finding the most stable adsorption geometry of a flexible molecule on a catalytic surface remains a key challenge due to the high dimensionality and ruggedness of the potential energy surface. We present a Gradient-Enhanced Genetic Algorithm (GE-GA) for the global optimization of adsorbate–surface configurations…
Authors not listed
Differential electrochemical mass spectrometry (DEMS) enables real time detection of volatile products formed at an electrode. However, its application in organic solvents is hindered by their volatility and by solvent-induced swelling or permeation of the membrane that defines the liquid/vacuum interface, compromising…
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…