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Metaheuristic optimization algorithms: a comprehensive overview and classification of benchmark test functions
This review aims to exploit a study on different benchmark test functions used to evaluate the performance of Meta-Heuristic (MH) optimization...
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Performance Analysis of Jaya Algorithm Using CEC’2013 Benchmark Functions
Jaya algorithm is population-based parameter less heuristic algorithm. The algorithm requires only control parameters like population size and a...
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Numeric Crunch Algorithm: a new metaheuristic algorithm for solving global and engineering optimization problems
In order to solve optimization problems, this paper introduces a new metaheuristic algorithm called the Numeric Crunch Algorithm (NCA), which employs...
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A general framework for improving cuckoo search algorithms with resource allocation and re-initialization
Cuckoo search (CS) has currently become one of the most favorable meta-heuristic algorithms (MHAs). In this article, a simple yet effective framework...
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Opposition-based learning multi-verse optimizer with disruption operator for optimization problems
Multi-verse optimizer (MVO) algorithm is one of the recent metaheuristic algorithms used to solve various problems in different fields. However, MVO...
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A swarm optimizer with attention-based particle sampling and learning for large scale optimization
Attention mechanism, which is a cognitive process of selectively concentrating on certain information while ignoring others, has been successfully...
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Nature-Inspired Metaheuristic Search Algorithms for Optimizing Benchmark Problems: Inclined Planes System Optimization to State-of-the-Art Methods
In the literature, different types of inclined planes system optimization (IPO) algorithms have been proposed and evaluated in various applications....
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A single-solution–compact hybrid algorithm for continuous optimization
This research paper proposes a memetic algorithm based on a hybridization of two metaheuristic approaches, a single-solution method and a compact...
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Convergence analysis of flow direction algorithm and its improvement
Flow direction algorithm (FDA) is a new physics-based optimization algorithm for solving global optimization problems. Although the FDA has shown...
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An Enhanced Beluga Whale Optimization Algorithm for Engineering Optimization Problems
This paper presents an enhanced beluga whale optimization algorithm (EBWOA) for engineering optimization problems. To enhance the performance and...
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A large-scale global optimization algorithm with a new adaptive computing resource allocation mechanism
Cooperative co-evolution (CC) algorithm is an evolutionary computational framework that can effectively solve high-dimensional optimization problems....
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A hybrid learning-based genetic and grey-wolf optimizer for global optimization
The grey-wolf optimizer (GWO) is a comparatively recent and competent algorithm in Swarm Intelligence (SI) to solve numerical and real-world...
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An efficient hybrid swarm intelligence optimization algorithm for solving nonlinear systems and clustering problems
This article proposes a new hybrid swarm intelligence optimization algorithm called monarch butterfly optimization (MBO) algorithm with cuckoo search...
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Improvement of the Fitness-Distance Balance-Based Supply–Demand Optimization Algorithm for Solving the Combined Heat and Power Economic Dispatch Problem
The CHPED scheduling problem involving a limited feasible operation region is considered to be one of the most basic nonlinear planning and operation...
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Performance Evaluation of Runner–Root Algorithm on CEC 2013 Benchmark Functions
From past four decades, many heuristic algorithms are proposed by researchers for solving complex engineering problems. The main source of...
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Reinforcement-learning-based parameter adaptation method for particle swarm optimization
Particle swarm optimization (PSO) is a well-known optimization algorithm that shows good performances in solving different optimization problems....
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Competitive teaching–learning-based optimization for multimodal optimization problems
Teaching–learning-based optimization is one of the latest metaheuristic algorithms. TLBO has a simple framework and good global search ability. In...
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The Golf Sport Inspired Search metaheuristic algorithm and the game theoretic analysis of its operators’ effectiveness
This paper introduces the Golf Sport Inspired Search (GSIS) algorithm as an evolutionary search method for numerical optimization. Each solution is...
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Self-adaptively commensal learning-based Jaya algorithm with multi-populations and its application
Jaya algorithm is an advanced optimization algorithm, which has been applied to many real-world optimization problems. Jaya algorithm has better...
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A Cooperative Evolution Framework Based on Fish Migration Optimization
The Fish Migration Optimization (FMO) method was inspired by the fish swim and migration behaviors and has been proofed to be a brilliant algorithm...