Everything about Metaheuristic
Optimization technique
In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, tune, or select a heuristic that may provide a sufficiently good solution to an optimization problem or a machine learning problem, especially with incomplete or imperfect information or limited computation capacity. Metaheuristics sample a subset of solutions which is otherwise too large to be completely enumerated or otherwise explored. Metaheuristics may make relatively few assumptions about the optimization problem being solved and so may be usable for a variety of problems. Their use is always of interest when exact or other (approximate) methods are not available or are not expedient, either because the calculation time is too long or because, for example, the solution provided is too imprecise. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: MetaheuristicA 5-minute orientation
- Skim a recent paper: Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problemsInfluential work since 2022
- Pick up a classic book: Handbook of Approximation Algorithms and MetaheuristicsThe most-reprinted book on the subject
- Read the landmark paper: Marine Predators Algorithm: A nature-inspired metaheuristicCited 2,331 times
- Go sideways: List of metaphor-based metaheuristicsA closely related topic
- Go sideways: Memetic algorithmA closely related topic
📖 Definitions
Noun An experimental heuristic method for solving a general class of computational problems by combining user procedures in the hope of obtaining a more efficient or robust procedure.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Marine Predators Algorithm: A nature-inspired metaheuristic
A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm
Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems
Water cycle algorithm – A novel metaheuristic optimization method for solving constrained engineering optimization problems
Symbiotic Organisms Search: A new metaheuristic optimization algorithm
African vultures optimization algorithm: A new nature-inspired metaheuristic algorithm for global optimization problems
Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems
Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization
🆕 Influential since 2022
Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems
Beluga whale optimization: A novel nature-inspired metaheuristic algorithm
An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges
Crested Porcupine Optimizer: A new nature-inspired metaheuristic
Kepler optimization algorithm: A new metaheuristic algorithm inspired by Kepler’s laws of planetary motion
📚 Books worth reading
Handbook of Approximation Algorithms and MetaheuristicsTeofilo F. Gonzalez · 2007- 📕Practical Approach to Metaheuristics Using LabVIEW and MATLAB®Pedro Ponce-Cruz, Arturo Molina Gutiérrez · 2020
- 📕Optimization of Integer/Fractional Order Chaotic Systems by Metaheuristics and Their Electronic RealizationEsteban Tlelo-Cuautle, Luis Gerardo de la Fraga · 2021
- 📕Metaheuristics for Resource Deployment under Uncertainty in Complex SystemsShuxin Ding, Chen Chen · 2021
- 📕Metaheuristic Computation with MATLAB®Erik Cuevas, Alma Rodriguez · 2020
Optimization Using Evolutionary Algorithms and MetaheuristicsKaushik Kumar, J. Paulo Davim · 2019- 📕Metaheuristic Algorithms in Industry 4. 0Pritesh Shah, Ravi Sekhar · 2021
- 📕Metaheuristic Approaches to Portfolio OptimizationJhuma Ray, Anirban Mukherjee · 2019
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- List of metaphor-based metaheuristics This is a chronologically ordered list of metaphor-based metaheuristics and swarm intelligence algorithms, sorted by decade of proposal. Simulated annealing…
- Memetic algorithm In computer science and operations research, a memetic algorithm (MA) is an extension of an evolutionary algorithm (EA) that aims to accelerate the evolutionary…
- Evolutionary algorithm Evolutionary algorithms (EA) reproduce essential elements of biological evolution in a computer algorithm in order to solve "difficult" problems, at least…
- Evolutionary computation Evolutionary computation (EC) from computer science is a family of algorithms for global optimization inspired by biological evolution, and a subfield…
- Simulated annealing Simulated annealing (SA) is a probabilistic technique for approximating the global optimum of a given function. Specifically, it is a metaheuristic to…
- Hyper-heuristic A hyper-heuristic is a heuristic search method that seeks to automate, often by the incorporation of machine learning techniques, the process of selecting…
- Genetic algorithm A genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA)…
- Greedy randomized adaptive search procedure The greedy randomized adaptive search procedure (also known as GRASP) is a metaheuristic algorithm commonly applied to combinatorial optimization problems…