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Statistically aided Binary Multi-Objective Grey Wolf Optimizer: a new feature selection approach for classification
Feature selection identifies the most relevant features that help improve the classifier’s performance. The Binary Multi-Objective Grey Wolf...
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Multi-objective Biological Survival Optimizer with Application in Engineering Problems
Biological survival optimizer is a recent proposed swarm-based optimization algorithm, which is inspired by the nature behavior of prey and has two...
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Improved Harris Hawks Optimizer with chaotic maps and opposition-based learning for task scheduling in cloud environment
Scheduling tasks in the cloud system is the main issue that needs to be addressed in order to improve customer satisfaction and system performance....
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Competitive binary multi-objective grey wolf optimizer for fast compact antenna topology optimization
We propose a competitive binary multi-objective grey wolf optimizer (CBMOGWO) to reduce the heavy computational burden of conventional...
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Gene-targeting multiplayer battle game optimizer for large-scale global optimization via cooperative coevolution
This paper proposes an efficient variant of the multiplayer battle game optimizer (MBGO) named gene-targeting MBGO (GTMBGO). We simplify the original...
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Boosting white shark optimizer for global optimization and cloud scheduling problem
With the growing adoption of cloud computing in both public and private sector enterprises, the industry has experienced rapid expansion. To fully...
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Tempura: a general cost-based optimizer framework for incremental data processing (Journal Version)
Incremental processing is widely adopted in many applications, ranging from incremental view maintenance, stream computing, to recently emerging...
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Reinforcement Learning-Based SPARQL Join Ordering Optimizer
In recent years, relational databases successfully leverage reinforcement learning to optimize query plans. For graph databases and RDF quad stores,...
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LTCSO/D: a large-scale tri-particle competitive swarm optimizer based on decomposition for multiobjective optimization
Large-scale multiobjective optimization problems (LSMOPs), whose exponentially expanded search space and conflicting objectives have brought great...
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Mountain gazelle optimizer for standalone hybrid power system design incorporating a type of incentive-based strategies
The main objective of this research study is to improve the performance of a standalone hybrid power system (SHPS) that consists of photovoltaic...
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Rules embedded harris hawks optimizer for large-scale optimization problems
Harris Hawks Optimizer (HHO) is a recent optimizer that was successfully applied for various real-world problems. However, working under large-scale...
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Chernobyl disaster optimizer (CDO): a novel meta-heuristic method for global optimization
This paper proposes a novel meta-heuristic optimization method, namely “Chernobyl Disaster Optimizer (CDO)”. The underlying concepts and principles...
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A MapReduce hybridized spotted hyena optimizer algorithm for travelling salesman problem
The Traveling Salesman (TSP) problem is one of the most common basic problems in the nondeterministic polynomial problems (NP-hard) category. TSP is...
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Scenario-Based Approach to Solve Optimal Reactive Power Dispatch Problem with Integration of Solar Energy Using Modified Ant Line Optimizer
This paper considers a scenario-based approach, a stochastic ORPD formulation and solution that accommodates uncertain load demand, and solar power....
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Identifying top-k influential nodes in social networks: a discrete hybrid optimizer by integrating butterfly optimization algorithm with differential evolution
The most challenge of influence maximization (IM) is to locate a finite set of influencers while maximizing the influence dissemination in a social...
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An efficient improved exponential distribution optimizer: application to the global, engineering and combinatorial optimization problems
Population-based meta-heuristic optimization algorithms play a vital role in addressing optimization problems. Nowadays, exponential distribution...
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An energy-adaptive clustering method based on Taguchi-based-GWO optimizer for wireless sensor networks with a mobile sink
In wireless sensor networks (WSNs), balancing energy consumption is always a critical problem. Multi-hop data transmission may cause the nodes around...
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Equilibrium optimizer-based harmony search algorithm with nonlinear dynamic domains and its application to real-world optimization problems
Harmony Search (HS) algorithm is a swarm intelligence algorithm inspired by musical improvisation. Although HS has been applied to various...
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A new hybrid algorithm based on golden eagle optimizer and grey wolf optimizer for 3D path planning of multiple UAVs in power inspection
As an emerging power inspection method, unmanned aerial vehicle (UAV) inspection has the advantages of high safety, high efficiency, and low cost. In...
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Optimized task scheduling in cloud computing using improved multi-verse optimizer
The multiverse optimizer (MVO) is one of the most trending algorithms used nowadays. The searching space in MVO is restricted by the best solution...
