17 papers · ranked by Valyu relevance
Konstantin Barkalov, Ilya Lebedev, Evgeny Kozinov, Alexander Gorban + 1 more
'Ivan Tyukin'] This paper features the study of global optimization problems and numerical methods of their solution. Such problems are computationally expensive since the objective function can be multi-extremal, nondifferentiable, and, as a rule, given in the form of a “black box”. This study used a deterministic…
Leilei Cao, Lihong Xu, Erik D. Goodman
A Guiding Evolutionary Algorithm (GEA) with greedy strategy for global optimization problems is proposed. Inspired by Particle Swarm Optimization, the Genetic Algorithm, and the Bat Algorithm, the GEA was designed to retain some advantages of each method while avoiding some disadvantages. In contrast to the usual…
Rahib H. Abiyev, Mustafa Tunay
A novel learning algorithm for solving global numerical optimization problems is proposed. The proposed learning algorithm is intense stochastic search method which is based on evaluation and optimization of a hypercube and is called the hypercube optimization (HO) algorithm. The HO algorithm comprises the…
Pradeep K Polisetty, Eberhard O Voit, Edward P Gatzke
Background The problem of estimating the parameters of dynamic models of complex biological systems from time series data is becoming increasingly important. Methods and results Particular consideration is given to metabolic systems that are formulated as Generalized Mass Action (GMA) models. The estimation problem is…
Delong Guo, Huajuan Huang, Yinggao Yue
The Honey Badger Algorithm (HBA) is a recently proposed metaheuristic optimization algorithm inspired by the foraging behavior of honey badgers. The search mechanism of this algorithm is divided into two phases: a mining phase and a honey-seeking phase, effectively emulating the processes of exploration and…
Tobias Keßler, Christian Kunde, Nick Mertens, Dennis Michaels + 1 more
'Achim Kienle'] Surrogate-based optimization of distillation columns using an iterative Kriging approach is investigated. Focus is on deterministic global optimization to avoid suboptimal local minima. The determination of optimal setups and operating conditions for ideal and non-ideal distillation columns, leading to…
Derek C. Manheim, Russell L. Detwiler
Title: Graphical abstract
Sundaram B. Pandya, Pradeep Jangir, Miroslav Mahdal, Kanak Kalita + 2 more
In this study, we tackle the challenge of optimizing the design of a Brushless Direct Current (BLDC) motor. Utilizing an established analytical model, we introduced the Multi-Objective Generalized Normal Distribution Optimization (MOGNDO) method, a biomimetic approach based on Pareto optimality, dominance, and external…
Mohammad Dehghani, Pavel Trojovský, Wojciech Kempa, Iwona Paprocka
Population-based optimization algorithms are one of the most widely used and popular methods in solving optimization problems. In this paper, a new population-based optimization algorithm called the Teamwork Optimization Algorithm (TOA) is presented to solve various optimization problems. The main idea in designing the…
Thanh Sang-To, Minh Hoang-Le, Magd Abdel Wahab, Thanh Cuong-Le
In this study, a meta-heuristic algorithm, named The Planet Optimization Algorithm (POA), inspired by Newton's gravitational law is proposed. POA simulates the motion of planets in the solar system. The Sun plays the key role in the algorithm as at the heart of search space. Two main phases, local and global search…
Megha Varshney, Pravesh Kumar, Musrrat Ali, Yonis Gulzar + 3 more
'Weiguo Zhao' 'Zhenxing Zhang'] The Aquila Optimizer (AO) is a metaheuristic algorithm that is inspired by the hunting behavior of the Aquila bird. The AO approach has been proven to perform effectively on a range of benchmark optimization issues. However, the AO algorithm may suffer from limited exploration ability in…
Mohammad Dehghani, Pavel Trojovský
In this paper, a new optimization algorithm called hybrid leader-based optimization (HLBO) is introduced that is applicable in optimization challenges. The main idea of HLBO is to guide the algorithm population under the guidance of a hybrid leader. The stages of HLBO are modeled mathematically in two phases of…
Omar Alsayyed, Tareq Hamadneh, Hassan Al-Tarawneh, Mohammad Alqudah + 5 more
'Saikat Gochhait' 'Irina Leonova' 'Om Parkash Malik' 'Mohammad Dehghani' 'Huiling Chen'] In this paper, a new bio-inspired metaheuristic algorithm called Giant Armadillo Optimization (GAO) is introduced, which imitates the natural behavior of giant armadillo in the wild. The fundamental inspiration in the design of GAO…
Florian Häse, Loïc M. Roch, Alán Aspuru-Guzik
Chimera enables multi-target optimization for experimentation or expensive computations, where evaluations are the limiting factor.
Mohammad Dehghani, Štěpán Hubálovský, Pavel Trojovský, Wojciech Kempa + 1 more
'Wojciech Kempa' 'Iwona Paprocka'] Numerous optimization problems designed in different branches of science and the real world must be solved using appropriate techniques. Population-based optimization algorithms are some of the most important and practical techniques for solving optimization problems. In this paper, a…
Lenin Kanagasabai
This paper proposes Pomarine jaeger Optimization (PJO) algorithm, Tiger hunting Optimization (THO) Algorithm, Desert Reynard and Vixen Inspired Optimization (DRVIO) Algorithm, Lonchodidae optimization (LO) algorithm, Caracal optimization (CO) algorithm, Barasingha optimization (BO) algorithm, Amur leopard optimization…
Waqar Younas, Gauhar Ali, Naveed Ahmad, Qamar Abbas + 6 more
'Muhammad Talha Masood' 'Asim Munir' 'Mohammed ElAffendi' 'Shah Nazir' 'Habib Ullah Khan' 'Iván García-Magariño'] Metaheuristic algorithms are effectively used in searching some optical solution space. for optical solution. It is basically the type of local search generalization that can provide useful solutions for…