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Advanced backtracking search for solving continuous optimization problems
This paper recommends develo** advanced backtracking search (ABS) to use single- and multi-vector mutation strategies to effectively enhance the...
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Solving Continuous Optimization Problems with a New Hyperheuristic Framework
Continuous optimization is a central task in computer science. Hyperheuristics prove to be an effective mechanism for intelligent operator selection...
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Solving Maxmin Optimization Problems via Population Games
Population games are games with a finite set of available strategies and an infinite number of players, in which the reward for choosing a given...
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Combining discrete and continuous information for multi-criteria optimization problems
In multi-criteria optimization problems that originate from real-world decision making tasks, we often find the following structure: There is an...
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Harmony-driven technique for solving optimization and engineering problems
Optimization techniques play a crucial role in improving the performance of machine learning applications. However, traditional techniques may not be...
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Learning cooking algorithm for solving global optimization problems
In recent years, many researchers have made a continuous effort to develop new and efficient meta-heuristic algorithms to address complex problems....
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Secretary bird optimization algorithm: a new metaheuristic for solving global optimization problems
This study introduces a novel population-based metaheuristic algorithm called secretary bird optimization algorithm (SBOA), inspired by the survival...
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Modified crayfish optimization algorithm for solving multiple engineering application problems
Crayfish Optimization Algorithm (COA) is innovative and easy to implement, but the crayfish search efficiency decreases in the later stage of the...
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Two modified Pascoletti–Serafini methods for solving multiobjective optimization problems and multiplicative programming problems
In this paper, a modified Pascoletti–Serafini scalarization approach, called MOP_MPS, is proposed to generate approximations of a Pareto front of...
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Bilevel-search particle swarm optimization algorithm for solving LSGO problems
Improving the efficiency of solving complex optimization problems is the focus of intelligent algorithm research in recent years. Complex...
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An Improved Golden Jackal Optimization Algorithm Based on Multi-strategy Mixing for Solving Engineering Optimization Problems
Nowadays, optimization techniques are required in various engineering domains to find optimal solutions for complex problems. As a result, there is a...
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A fuzzy reinforced Jaya algorithm for solving mathematical and structural optimization problems
Jaya is a metaheuristic algorithm that uses a pair of random internal parameters to adjust its exploration and exploitation search behaviors. Such a...
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Improved Salp swarm algorithm for solving single-objective continuous optimization problems
The Salp Swarm Algorithm (SSA) is an effective single-objective optimization algorithm that was inspired by the navigating and foraging behaviors of...
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Diversity enhanced Equilibrium Optimization algorithm for solving unconstrained and constrained optimization problems
This research study proposes a novel mutation scheme mainly based on the manipulation equations of Tangent Search Optimization and mutualism phase of...
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Nature-Inspired Heuristic Frameworks Trends in Solving Multi-objective Engineering Optimization Problems
Nowadays, nature-inspired artificial intelligent metaheuristic optimization algorithms (MHOAs) have gained many attentions from researchers all over...
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A novel two-phase trigonometric algorithm for solving global optimization problems
Metaheuristics play a major role in the important domain of global optimization. Since they are problem independent, they can be effectively used in...
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Convergence of Continuous Analogues of Numerical Methods for Solving Degenerate Optimization Problems and Systems of Nonlinear Equations
AbstractA new approach is proposed for studying the convergence of continuous analogues of the gradient and Newton methods as applied to degenerate...
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A nature-inspired meta-heuristic knowledge-based algorithm for solving multiobjective optimization problems
The effectiveness of meta-heuristics has recently been well demonstrated. However, there will be a need for reliable algorithms that can handle...
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IHHO: an improved Harris Hawks optimization algorithm for solving engineering problems
Harris Hawks optimization (HHO) algorithm was a powerful metaheuristic algorithm for solving complex problems. However, HHO could easily fall within...
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Hybrid Strategies Based Seagull Optimization Algorithm for Solving Engineering Design Problems
The seagull optimization algorithm (SOA) is a meta-heuristic algorithm proposed in 2019. It has the advantages of structural simplicity, few...
