Recent advances in Grey Wolf Optimizer, its versions and applications
The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
A hyperheuristic with Q-learning for the multiobjective energy-efficient distributed blocking flow shop scheduling problem
F Zhao, S Di, L Wang - IEEE Transactions on Cybernetics, 2022 - ieeexplore.ieee.org
Carbon peaking and carbon neutrality, which are the significant national strategy for
sustainable development, have attracted considerable attention from production enterprises …
sustainable development, have attracted considerable attention from production enterprises …
Application of variational mode decomposition and chaotic grey wolf optimizer with support vector regression for forecasting electric loads
Z Zhang, WC Hong - Knowledge-Based Systems, 2021 - Elsevier
Accurate electric load forecasting is critical in guaranteeing the efficiency of the load
dispatch and supply by a power system, which prevents the wasting of electricity and …
dispatch and supply by a power system, which prevents the wasting of electricity and …
Hybrid Aquila optimizer with arithmetic optimization algorithm for global optimization tasks
Many population-dependent solutions have recently been suggested. Despite their
widespread adoption in many applications, we are still researching using suggested …
widespread adoption in many applications, we are still researching using suggested …
A survey of swarm intelligence based load balancing techniques in cloud computing environment
Cloud computing offers flexible, interactive, and observable access to shared resources on
the Internet. It frees users from the requirements of managing computing on their hardware. It …
the Internet. It frees users from the requirements of managing computing on their hardware. It …
Opposition-based learning grey wolf optimizer for global optimization
X Yu, WY Xu, CL Li - Knowledge-Based Systems, 2021 - Elsevier
Grey wolf optimizer is a novel swarm intelligent algorithm. It has received lots of interest from
the heuristic algorithm community for its superior optimization capacity and few parameters …
the heuristic algorithm community for its superior optimization capacity and few parameters …
Opposition-based Laplacian distribution with Prairie Dog Optimization method for industrial engineering design problems
Abstract Prairie Dog Optimization is a population-based optimization method that uses the
behavior of prairie dogs to find the optimal solution. This paper proposes a novel …
behavior of prairie dogs to find the optimal solution. This paper proposes a novel …
Optimum design of a seat bracket using artificial neural networks and dandelion optimization algorithm
Nature-inspired metaheuristic algorithms are gaining popularity with their easy applicability
and ability to avoid local optimum points, and they are spreading to wide application areas …
and ability to avoid local optimum points, and they are spreading to wide application areas …
Binary improved white shark algorithm for intrusion detection systems
Intrusion Detection (ID) is an essential task in the cyberattacks domain built to secure
Internet applications and networks from malicious actors. The main shortcoming of the …
Internet applications and networks from malicious actors. The main shortcoming of the …
Island-based Cuckoo Search with elite opposition-based learning and multiple mutation methods for solving optimization problems
BH Abed-alguni, D Paul - Soft Computing, 2022 - Springer
Abstract The island Cuckoo Search (i CSPM) algorithm is a variation of Cuckoo Search that
uses the island model and highly disruptive polynomial mutation to solve optimization …
uses the island model and highly disruptive polynomial mutation to solve optimization …