Search Results - "Population-based algorithms"

Infeasibility and structural bias in differential evolution by Caraffini, Fabio, Kononova, Anna V., Corne, David

“…Structural bias is a recently identified property of optimisation algorithms, causing them to favour certain regions of the search space over others,…”
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Advances in Sine Cosine Algorithm: A comprehensive survey by Abualigah, Laith, Diabat, Ali

“…The Sine Cosine Algorithm (SCA) is a population-based optimization algorithm introduced by Mirjalili in 2016, motivated by the trigonometric sine and cosine…”
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A hybrid self-adaptive sine cosine algorithm with opposition based learning by Gupta, Shubham, Deep, Kusum

“…•A new method to solve global optimization and engineering problems called m-SCA.•The m-SCA improves the SCA using self-adaptation and opposition based…”
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Multi-population estimation of distribution algorithm for multilevel thresholding in image segmentation by Ramos-Frutos, Jorge, Oliva, Diego, Miguel-Andrés, Israel, Casas-Ordaz, Angel, Ramos-Soto, Oscar, Aranguren, Itzel, Zapotecas-Martínez, Saúl

“…Optimization algorithms are crucial for solving complex optimization problems in fields such as image processing. Image segmentation is complicated and…”
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A memory guided sine cosine algorithm for global optimization by Gupta, Shubham, Deep, Kusum, Engelbrecht, Andries P.

“…Real-world optimization problems demand an algorithm which properly explores the search space to find a good solution to the problem. The sine cosine algorithm…”
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Improved sine cosine algorithm with crossover scheme for global optimization by Gupta, Shubham, Deep, Kusum

“…Sine Cosine Algorithm is a recently developed algorithm based on the characteristics of sine and cosine trigonometric functions, to solve global optimization…”
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Holistic swarm optimization: A novel metaphor-less algorithm guided by whole population information for addressing exploration-exploitation dilemma by Akbari, Ebrahim, Rahimnejad, Abolfazl, Gadsden, Stephen Andrew

“…•Introduces Holistic Swarm Optimization (HSO), a novel metaphorless optimization algorithm.•HSO utilizes entire population data for robust and informed search…”
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Attraction–Repulsion Optimization Algorithm for Global Optimization Problems by Cymerys, Karol, Oszust, Mariusz

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A multi-objective algorithm for optimization of modern machining processes by Rao, R. Venkata, Rai, Dhiraj P., Balic, Joze

“…Multi-objective optimization aspects of four modern machining processes namely wire-electro discharge machining process, laser cutting process, electrochemical…”
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GA-GOA hybrid algorithm and comparative study of different metaheuristic population-based algorithms for solar tower heliostat field design by Arrif, Toufik, Hassani, Samir, Guermoui, Mawloud, Sánchez-González, A., A.Taylor, Robert, Belaid, Abdelfetah

“…A comparative analysis has been carried out between eight metaheuristic algorithms, namely; genetic algorithm (GA), differential evolution (DE), particle swarm…”
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A hybridization approach with predicted solution candidates for improving population-based optimization algorithms by Oszust, Mariusz, Sroka, Grzegorz, Cymerys, Karol

“…•A hybridization approach for improving population-based meta-heuristics is proposed.•The worst candidates in a population are replaced by predicted…”
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Meta-optimization of multi-objective population-based algorithms using multi-objective performance metrics by Łapa, Krystian

“…In this paper, a method for optimizing the parameters of multi-objective population-based algorithms is proposed. It is based on a meta-optimization, in which…”
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A supervised parallel optimisation framework for metaheuristic algorithms by Muttio, Eugenio J., Dettmer, Wulf G., Clarke, Jac, Perić, Djordje, Ren, Zhaoxin, Fletcher, Lloyd

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Electric fish optimization: a new heuristic algorithm inspired by electrolocation by Yilmaz, Selim, Sen, Sevil

“…Swarm behaviors in nature have inspired the emergence of many heuristic optimization algorithms. They have attracted much attention, particularly for complex…”
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A new optimization algorithm based on mimicking the voting process for leader selection by Trojovský, Pavel, Dehghani, Mohammad

“…Stochastic-based optimization algorithms are effective approaches to addressing optimization challenges. In this article, a new optimization algorithm called…”
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Simple population-based algorithms for solving optimization problems by Baskar, Amaladosan

“…Heuristic algorithms are simple yet powerful tools that are capable of yielding acceptable results in a reasonable execution time. Hence, they are being…”
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A particle swarm inspired approach for continuous distributed constraint optimization problems by Choudhury, Moumita, Sarker, Amit, Yaser, Samin, Khan, Md. Maruf Al Alif, Yeoh, William, Khan, Md. Mosaddek

“…Distributed Constraint Optimization Problems (DCOPs) are a widely studied framework for coordinating interactions in cooperative multi-agent systems. In…”
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Clustered Routing Method in the Internet of Things Using a Moth‐Flame Optimization Algorithm by Sadrishojaei, Mahyar, Jafari Navimipour, Nima, Reshadi, Midia, Hosseinzadeh, Mehdi

“…Summary Internet of Things (IoT) is a set of interrelated devices on the Internet platform that can receive and send data to make human life more efficient and…”
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The novel combination lock algorithm for improving the performance of metaheuristic optimizers by Bahreininejad, Ardeshir, Taib, Hasnanizan

“…•A novel method to improve the performance of population-based optimizers.•The combination lock algorithm used as a pre-processing optimization method.•The…”
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Generalized Net Model of Coyote Optimization Algorithm by Roeva, Olympia, Zoteva, Dafina, Vassilev, Peter

“…In the presented paper, the functioning of the coyote optimization algorithm (COA) is described using the apparatus of generalized nets (GNs). The COA is a…”
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