12 papers · ranked by Valyu relevance
L. M. Rasdi Rere, Mohamad Ivan Fanany, Aniati Murni Arymurthy
A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metaheuristic for accuracy improvement on convolution neural networks…
Ramazan Ozkan, Ruya Samli, Bilal Alatas
Metaheuristic algorithms are an important area of research that provides significant advances in solving complex optimization problems within acceptable time periods. Since the performances of these algorithms vary for different types of problems, many studies have been and need to be done to propose different…
Zoran Jakšić, Swagata Devi, Olga Jakšić, Koushik Guha + 3 more
The application of artificial intelligence in everyday life is becoming all-pervasive and unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired algorithms for multiparameter optimization, which find their use in a large number of areas. Novel methods and advances are being published at…
Junhao Wei, Yanzhao Gu, Zhanxi Xie, Yuzheng Yan + 6 more
'Zikun Li' 'Ngai Cheong' 'Jiafeng Zhang' 'Song Zhang' 'Seyedali Mirjalili'] Whale Optimization Algorithm (WOA) suffers from issues such as premature convergence, low population diversity in the later stages of iteration, slow convergence rate, low convergence accuracy, and an imbalance between exploration and…
Essam H. Houssein, Mohamed Hossam Abdel Gafar, Naglaa Fawzy, Ahmed Y. Sayed
'Ahmed Y. Sayed'] In this study, a novel hybrid metaheuristic algorithm, termed (BES-GO), is proposed for solving benchmark structural design optimization problems, including welded beam design, three-bar truss system optimization, minimizing vertical deflection in an I-beam, optimizing the cost of tubular columns, and…
Sarada Mohapatra, Prabhujit Mohapatra
A novel bio-inspired meta-heuristic algorithm, namely the American zebra optimization algorithm (AZOA), which mimics the social behaviour of American zebras in the wild, is proposed in this study. American zebras are distinguished from other mammals by their distinct and fascinating social character and leadership…
Abdelazim G. Hussien, Adrian Pop, Sumit Kumar, Fatma A. Hashim + 3 more
'Gang Hu' 'Yongquan Zhou' 'Shuai Li'] The Artificial Electric Field Algorithm (AEFA) stands out as a physics-inspired metaheuristic, drawing inspiration from Coulomb’s law and electrostatic force; however, while AEFA has demonstrated efficacy, it can face challenges such as convergence issues and suboptimal solutions…
Changin Oh, Kathleen P. Wilkie
We present the Toroidal Search Algorithm (TSA), a novel population-based metaheuristic optimization method inspired by the topology of a torus. Conventional metaheuristics frequently suffer from boundary stagnation, a phenomenon that severely degrades performance in bounded and high-dimensional search spaces. TSA…
Martín Gutiérrez, Yerko Ortiz, Javier Carrión
Metaheuristic procedures (MH) have been a trend driving Artificial Intelligence (AI) researchers for the past 50 years. A variety of tools and applications (not only in Computer Science) stem from these techniques. Also, MH frequently rely on evolution, a trademark process involved in cell colony growth. Generally, MH…
Andrea Polo-Rodríguez, David R. Penas, Julio R. Banga
Parameter estimation is a central challenge in systems biology, particularly for large dynamic models described by nonlinear ordinary differential equations (ODEs). These global optimization problems exhibit landscapes which are topologically heterogeneous, often exhibiting a pathological mixture of stiff, smooth…
Paul Bello, Pedro Gallardo, Lorena Pradenas, Jacques A. Ferland + 1 more
Childhood obesity is an undeniable reality and has shown a rapid growth in many countries. Obesity at an early age not only increases the risks of chronic diseases but also produces a problem for the whole healthcare system. One way to alleviate this problem is to provide each patient with an appropriate menu that can…
Dogan Corus, Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre
Understanding how the time-complexity of evolutionary algorithms (EAs) depend on their parameter settings and characteristics of fitness landscapes is a fundamental problem in evolutionary computation. Most rigorous results were derived using a handful of key analytic techniques, including drift analysis. However…