Cuckoo Search
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Cuckoo Search
In operations research, cuckoo search is an optimization algorithm developed by Xin-She Yang and Suash Deb in 2009. It was inspired by the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of host birds of other species. Some host birds can engage direct conflict with the intruding cuckoos. For example, if a host bird discovers the eggs are not their own, it will either throw these alien eggs away or simply abandon its nest and build a new nest elsewhere. Some cuckoo species such as the New World brood-parasitic Tapera have evolved in such a way that female parasitic cuckoos are often very specialized in the mimicry in colors and pattern of the eggs of a few chosen host species. Cuckoo search idealized such breeding behavior, and thus can be applied for various optimization problems. It has been shown that cuckoo search is a special case of the well-known (μ + λ)-evolution strategy. Metaphor Cuckoo search (CS) uses the following representation ...
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Operations Research
Operations research ( en-GB, operational research) (U.S. Air Force Specialty Code: Operations Analysis), often shortened to the initialism OR, is a discipline that deals with the development and application of analytical methods to improve decision-making. It is considered to be a subfield of mathematical sciences. The term management science is occasionally used as a synonym. Employing techniques from other mathematical sciences, such as modeling, statistics, and optimization, operations research arrives at optimal or near-optimal solutions to decision-making problems. Because of its emphasis on practical applications, operations research has overlap with many other disciplines, notably industrial engineering. Operations research is often concerned with determining the extreme values of some real-world objective: the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost). Originating in military efforts before World War II, its techniques have grown to ...
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Optimization (mathematics)
Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems of sorts arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries. In the more general approach, an optimization problem consists of maximizing or minimizing a real function by systematically choosing input values from within an allowed set and computing the value of the function. The generalization of optimization theory and techniques to other formulations constitutes a large area of applied mathematics. More generally, optimization includes finding "best available" values of some objective function given a define ...
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Algorithm
In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific Computational problem, problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can perform automated deductions (referred to as automated reasoning) and use mathematical and logical tests to divert the code execution through various routes (referred to as automated decision-making). Using human characteristics as descriptors of machines in metaphorical ways was already practiced by Alan Turing with terms such as "memory", "search" and "stimulus". In contrast, a Heuristic (computer science), heuristic is an approach to problem solving that may not be fully specified or may not guarantee correct or optimal results, especially in problem domains where there is no well-defined correct or optimal result. As an effective method, an algorithm ca ...
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Xin-She Yang
Xin-She Yang is Reader at the Middlesex University and was a senior research scientist at National Physical Laboratory, best known as a developer of various heuristic algorithms for engineering optimization. He obtained a DPhil in applied mathematics from Oxford University. He has given invited keynote talks at SEA2011, SCET2012, BIOMA2012 and Mendel Conference on Soft Computing (Mendel 2012). He has been elected as a Fellow of the Institute of Mathematics and its Application in 2021. He has been on the prestigious list of Highly Cited Researchers since 2016 by Clarivate Analyatics/Web of Science. Algorithms He created the firefly algorithm (2008), cuckoo search (2009), bat algorithm (2010),Yang X.-S., A New Metaheuristic Bat-Inspired Algorithm, in: Nature Inspired Cooperative Strategies for Optimization (NISCO 2010) (Eds. J. R. Gonzalez et al.), Studies in Computational Intelligence, Springer Berlin, 284, Springer, 65–74 (2010) and flower pollination algorithm (2012). ...
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Obligate Parasite
An obligate parasite or holoparasite is a parasitic organism that cannot complete its life-cycle without exploiting a suitable host. If an obligate parasite cannot obtain a host it will fail to reproduce. This is opposed to a facultative parasite, which can act as a parasite but does not rely on its host to continue its life-cycle. Obligate parasites have evolved a variety of parasitic strategies to exploit their hosts. Holoparasites and some hemiparasites are obligate. It is advantageous for the parasite to preserve the health of their host when this is compatible with their nutritional and reproductive requirements, except when the death of the host is necessary for transmission.Combes, C. (1997) Fitness of Parasites: Pathology and Selection ''International Journal for Parasitology'' 27 (1): 1–10. Species Obligate parasitism is exhibited in a range of organisms, with examples in viruses, bacteria, fungi, plants, and animals.Balashov, Yu.S. (2011) Parasitism and Ecological Paras ...
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Cuckoo
Cuckoos are birds in the Cuculidae family, the sole taxon in the order Cuculiformes . The cuckoo family includes the common or European cuckoo, roadrunners, koels, malkohas, couas, coucals and anis. The coucals and anis are sometimes separated as distinct families, the Centropodidae and Crotophagidae respectively. The cuckoo order Cuculiformes is one of three that make up the Otidimorphae, the other two being the turacos and the bustards. The family Cuculidae contains 150 species which are divided into 33 genera. The cuckoos are generally medium-sized slender birds. Most species live in trees, though a sizeable minority are ground-dwelling. The family has a cosmopolitan distribution; the majority of species are tropical. Some species are migratory. The cuckoos feed on insects, insect larvae and a variety of other animals, as well as fruit. Some species are brood parasites, laying their eggs in the nests of other species and giving rise to the metaphor ''cuckoo's egg'', ...
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New World
The term ''New World'' is often used to mean the majority of Earth's Western Hemisphere, specifically the Americas."America." ''The Oxford Companion to the English Language'' (). McArthur, Tom, ed., 1992. New York: Oxford University Press, p. 33: "[16c: from the feminine of ''Americus'', the Latinized first name of the explorer Amerigo Vespucci (1454–1512). The name ''America'' first appeared on a map in 1507 by the German cartographer Martin Waldseemüller, referring to the area now called Brazil]. Since the 16c, a name of the western hemisphere, often in the plural ''Americas'' and more or less synonymous with ''the New World''. Since the 18c, a name of the United States of America. The second sense is now primary in English: ... However, the term is open to uncertainties: ..." The term gained prominence in the early 16th century, during Europe's Age of Discovery, shortly after the Italian explorer Amerigo Vespucci concluded that America (now often called ''the Am ...
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Evolution Strategy
In computer science, an evolution strategy (ES) is an optimization technique based on ideas of evolution. It belongs to the general class of evolutionary computation or artificial evolution methodologies. History The 'evolution strategy' optimization technique was created in the early 1960s and developed further in the 1970s and later by Ingo Rechenberg, Hans-Paul Schwefel and their co-workers. Methods Evolution strategies use natural problem-dependent representations, and primarily mutation and selection, as search operators. In common with evolutionary algorithms, the operators are applied in a loop. An iteration of the loop is called a generation. The sequence of generations is continued until a termination criterion is met. For real-valued search spaces, mutation is performed by adding a normally distributed random vector. The step size or mutation strength (i.e. the standard deviation of the normal distribution) is often governed by self-adaptation (see evolution window). ...
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Lévy Flight
A Lévy flight is a random walk in which the step-lengths have a Lévy distribution, a probability distribution that is heavy-tailed. When defined as a walk in a space of dimension greater than one, the steps made are in isotropic random directions. Later researchers have extended the use of the term "Lévy flight" to also include cases where the random walk takes place on a discrete grid rather than on a continuous space. The term "Lévy flight" was coined by Benoît Mandelbrot, who used this for one specific definition of the distribution of step sizes. He used the term Cauchy flight for the case where the distribution of step sizes is a Cauchy distribution, and Rayleigh flight for when the distribution is a normal distribution (which is not an example of a heavy-tailed probability distribution). The particular case for which Mandelbrot used the term "Lévy flight" is defined by the survivor function of the distribution of step-sizes, ''U'', being :\Pr(U>u) = \begin 1 &:\ u ...
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Random Walk
In mathematics, a random walk is a random process that describes a path that consists of a succession of random steps on some mathematical space. An elementary example of a random walk is the random walk on the integer number line \mathbb Z which starts at 0, and at each step moves +1 or −1 with equal probability. Other examples include the path traced by a molecule as it travels in a liquid or a gas (see Brownian motion), the search path of a foraging animal, or the price of a fluctuating stock and the financial status of a gambler. Random walks have applications to engineering and many scientific fields including ecology, psychology, computer science, physics, chemistry, biology, economics, and sociology. The term ''random walk'' was first introduced by Karl Pearson in 1905. Lattice random walk A popular random walk model is that of a random walk on a regular lattice, where at each step the location jumps to another site according to some probability distribution. In a ...
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Pseudo-code
In computer science, pseudocode is a plain language description of the steps in an algorithm or another system. Pseudocode often uses structural conventions of a normal programming language, but is intended for human reading rather than machine reading. It typically omits details that are essential for machine understanding of the algorithm, such as variable declarations and language-specific code. The programming language is augmented with natural language description details, where convenient, or with compact mathematical notation. The purpose of using pseudocode is that it is easier for people to understand than conventional programming language code, and that it is an efficient and environment-independent description of the key principles of an algorithm. It is commonly used in textbooks and scientific publications to document algorithms and in planning of software and other algorithms. No broad standard for pseudocode syntax exists, as a program in pseudocode is not an executa ...
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