Various criteria can be used to classify the meta-algorithms:
Based on a population-based answer and a population-based algorithm, an answer-based algorithm changes an answer while the search process, while population-based algorithms during a search are considered as a population of responses.
Inspired by nature and without inspiration from nature: Many of the superconductive algorithms are inspired by nature, while some of the superconductive algorithms are not inspired by nature.
With memory and no memory: Some meta-algorithms lack memory, which means that these types of algorithms do not use information obtained during the search (eg, simulated refrigeration). This is while using some of the meta-bogus algorithms such as banned search memory. It stores the information it gains during the search.
Conclusive and probable: A definite superconpreting algorithm, such as banned search, solves the problem using definitive decisions. But in probable multi-platform algorithms such as simulated refrigeration, a series of possible rules are used during the search.
Methuristic Algorithms
1. Metaheuristic Optimization - Scholarpediawww.scholarpedia.org/article/Metaheuristic_Optimization Oct 21, 2011 · Metaheuristic optimization deals with optimization problems using metaheuristic algorithms. Optimization is essentially everywhere, from engineering design ...Heuristic algorithms - optimization
https://optimization.mccormick.northwestern.edu/index.php/...
Example Algorithms. The following are well-known examples of “intelligent” algorithms that use clever simplifications and methods to solve computationally complex ...
2. Heuristic Algorithms. - Πανεπιστήμιο Πατρώνstudents.ceid.upatras.gr/~papagel/project/kef5_5.htm The term heuristic is used for algorithms which find solutions among all possible ones ,but they do not guarantee that the best will be found,therefore they may be ...
3. metaheuristic-algorithms-python 0.1.6 : Python Package Index
https://pypi.python.org/pypi/metaheuristic-algorithms-python/0.1.6
Various metaheuristic algorithms implemented in Python # MetaheuristicAlgorithmsPython Various metaheuristic algorithms implemented in Python. This is equivalent to ...
Dennis
Dennis Mazur
If you mean metaheuristics, it is a higher level procedure of heuristic used to solve mathematical optimization problems that are NP hard, for example. Generally speaking, it gives good solution in reasonable computation time. For, example, Genetic algorithm, Particle swarm optimization, Ant colony optimization, Simulated annealing, etc.
They have plenty of applications in several fields, especially the optimization problems such as travel salesman problem, Knapsack problem, scheduling problems, etc.
Assalamu alaykum
The following paper is the most recent and most comprehensive study I have seen about metaheuristic techniques.
Article Metaheuristic research: a comprehensive survey
In addition, the following book is a recent reference that contains some applications a developments in this research area.
Book Recent developments of metaheuristics
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