Performance assessment of the metaheuristic optimization algorithms: an exhaustive review

AH Halim, I Ismail, S Das - Artificial Intelligence Review, 2021‏ - Springer
The simulation-driven metaheuristic algorithms have been successful in solving numerous
problems compared to their deterministic counterparts. Despite this advantage, the …

The coral reefs optimization algorithm: a novel metaheuristic for efficiently solving optimization problems

S Salcedo-Sanz, J Del Ser… - The Scientific World …, 2014‏ - Wiley Online Library
This paper presents a novel bioinspired algorithm to tackle complex optimization problems:
the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral …

An Efficiency Boost for Genetic Algorithms: Initializing the GA with the Iterative Approximate Method for Optimizing the Traveling Salesman Problem—Experimental …

E Alkafaween, A Hassanat, E Essa, S Elmougy - Applied Sciences, 2024‏ - mdpi.com
The genetic algorithm (GA) is a well-known metaheuristic approach for dealing with complex
problems with a wide search space. In genetic algorithms (GAs), the quality of individuals in …

Solving TSP by using combinatorial Bees algorithm with nearest neighbor method

M Sahin - Neural Computing and Applications, 2023‏ - Springer
Bees Algorithm (BA) is a popular meta-heuristic method that has been used in many
different optimization areas for years. In this study, a new version of combinatorial BA is …

Golden ball: a novel meta-heuristic to solve combinatorial optimization problems based on soccer concepts

E Osaba, F Diaz, E Onieva - Applied intelligence, 2014‏ - Springer
In this paper, a new multiple population based meta-heuristic to solve combinatorial
optimization problems is introduced. This meta-heuristic is called Golden Ball (GB), and it is …

An improved genetic algorithm with a new initialization mechanism based on regression techniques

AB Hassanat, VBS Prasath, MA Abbadi, SA Abu-Qdari… - Information, 2018‏ - mdpi.com
Genetic algorithm (GA) is one of the well-known techniques from the area of evolutionary
computation that plays a significant role in obtaining meaningful solutions to complex …

Performance analyses over population seeding techniques of the permutation-coded genetic algorithm: An empirical study based on traveling salesman problems

PV Paul, N Moganarangan, SS Kumar, R Raju… - Applied soft …, 2015‏ - Elsevier
The genetic algorithm (GA) is a population based meta-heuristic global optimization
technique for dealing with complex problems with very large search space. The population …

Adaptive experience engine for serious games

F Bellotti, R Berta, A De Gloria… - IEEE Transactions on …, 2009‏ - ieeexplore.ieee.org
Designing games that support knowledge and skill acquisition has become a promising
frontier of education techniques, since games are able to capture the user concentration for …

Bee colony optimization with local search for traveling salesman problem

LP Wong, MYH Low, CS Chong - International Journal on Artificial …, 2010‏ - World Scientific
Many real world industrial applications involve the Traveling Salesman Problem (TSP),
which is a problem that finds a Hamiltonian path with minimum cost. Examples of problems …

A new population seeding technique for permutation-coded Genetic Algorithm: Service transfer approach

PV Paul, A Ramalingam, R Baskaran… - Journal of …, 2014‏ - Elsevier
Genetic Algorithm (GA) is a popular heuristic method for dealing complex problems with very
large search space. Among various phases of GA, the initial phase of population seeding …