Results 11 to 20 of about 53,710 (343)
A Hybrid Optimization Framework with Dynamic Transition Scheme for Large-Scale Portfolio Management
Algorithms, 2022 Meta-heuristic algorithms have successfully solved many real-world problems in recent years. Inspired by different natural phenomena, the algorithms with special search mechanisms can be good at tackling certain problems.
Zhenglong Li, Vincent Tam
doaj +1 more source
Meta-heuristics for portfolio optimization
Soft Computing, 2023 AbstractPortfolio optimization has been studied extensively by researchers in computer science and finance, with new and novel work frequently published. Traditional methods, such as quadratic programming, are not computationally effective for solving complex portfolio models.
Kyle Erwin, Andries P. Engelbrecht
openaire +1 more source
A comprehensive review on meta-heuristic algorithms and their classification with novel approach
Journal of Applied Research on Industrial Engineering, 2021 Conventional and classical optimization methods are not efficient enough to deal with complicated, NP-hard, high-dimensional, non-linear, and hybrid problems.
Hojatollah Rajabi Moshtaghi +2 more
doaj +1 more source
Benchmarking Meta-heuristic Optimization
International Journal of Advanced Networking and Applications, 2020 Solving an optimization task in any domain is a very challenging problem, especially when dealing with nonlinear problems and non-convex functions. Many meta-heuristic algorithms are very efficient when solving nonlinear functions. A meta-heuristic algorithm is a problem-independent technique that can be applied to a broad range of problems.
Mona Nasr +5 more
openaire +2 more sources
An Opposition-Based Chaotic Salp Swarm Algorithm for Global Optimization
IEEE Access, 2020 The salp swarm algorithm (SSA) is a bio-heuristic optimization algorithm proposed in 2017. It has been proved that SSA has competitive results compared to several other well-known meta-heuristic algorithms on various optimization problem.
Xiaoqiang Zhao +3 more
doaj +1 more source
Review of Quantum-inspired Metaheuristic Algorithms and Its Applications [PDF]
Jisuanji kexueThe quantum meta heuristic algorithm is developed by applying quantum computing to the meta-heuristic algorithm.This kind of algorithm is good at solving combinatorial and numerical optimization problems,and has the characteristics of acce-lerated ...
RUAN Ning, LI Chun, MA Haoyue, JIA Yi, LI Tao
doaj +1 more source
Mathematics, 2022 The agile earth observation satellite scheduling problem (AEOSSP), as a time-dependent and arduous combinatorial optimization problem, has been intensively studied in the past decades.
Jiawei Chen +4 more
doaj +1 more source
Meta-heuristic algorithms in car engine design: a literature survey [PDF]
, 2015 Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy.
Tayarani-N, Mohammad-H. +2 more
core +2 more sources
Alexandria Engineering Journal, 2023 Meta heuristics is an optimization approach that works as an intelligent technique to solve optimization problems. Evolutionary algorithms, human-based algorithms, physics-based algorithms and swarm intelligence are categorized under meta-heuristic ...
Othman Waleed Khalid +2 more
doaj +1 more source
Meta-heuristic optimization methods applied to renewable distributed generation planning: A review [PDF]
E3S Web of Conferences, 2021 Due to its proven efficiency and computational speed, the most recent developed meta-heuristic optimization methods are widely used to better integrate renewable distributed generation (RDG) into the electricity grid.
Tarraq Ali +3 more
doaj +1 more source