14 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…
Dler O. Hasan, Hardi M. Mohammed, Zrar Kh. Abdul
The FOX optimizer, inspired by red fox hunting behavior, is a powerful algorithm for solving real-world and engineering problems. However, despite balancing exploration and exploitation, it can prematurely converge to local optima, as agent positions are updated solely based on the current best-known position, causing…
Zhongqiang Ma, Guohua Wu, Ponnuthurai Nagaratnam Suganthan, Aijuan Song + 1 more
'Aijuan Song' 'Qizhang Luo'] Abstract: Metaheuristics are popularly used in various fields, and they have attracted much attention in the scientific and industrial communities. In recent years, the number of new metaheuristic names has been continuously growing. Generally, the inventors attribute the novelties of these…
Abhilash Singh, Seyed Muhammad Hossein Mousavi, Kumar Gaurav
We introduced the Scorpion Hunting Strategy (SHS), a novel population-based, nature-inspired optimisation algorithm. This algorithm draws inspiration from the hunting strategy of scorpions, which identify, locate, and capture their prey using the alpha and beta vibration operators. These operators control the SHS…
Rubén Ruiz-Torrubiano
Local search metaheuristics like tabu search or simulated annealing are popular heuristic optimization algorithms for finding near-optimal solutions for combinatorial optimization problems. However, it is still challenging for researchers and practitioners to analyze their behaviour and systematically choose one over a…
Salar Farahmand‐Tabar
> Abstract. Metaheuristics are stochastic optimization algorithms that mimic natural processes to find optimal solutions to complex problems. The success of metaheuristics largely depends on the ability to effectively explore and exploit the search space. Memory mechanisms have been introduced in several popular…
Kenneth Sörensen, Marc Sevaux, Fred Glover
Even though people have used heuristics throughout history, and the human brain is equipped with a formidable heuristic engine to solve an enormous array of challenging optimization problems, the scientific study of heuristics (and, by extension, metaheuristics) is a relatively young endeavour. It is not an…
Carlos Afonso Rocha da Silva Júnior, Roberto Yuji Tanaka, Luiz Carlos Farias da Silva, Angelo Pássaro
symmetric TSP: a comparative study Authors: ['Carlos Afonso Rocha da Silva Júnior' 'Roberto Yuji Tanaka' 'Luiz Carlos Farias da Silva' 'Angelo Pássaro'] The Travelling Salesman Problem - TSP is one of the most explored problems in the scientific literature to solve real problems regarding the economy, transportation…