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A hybrid genetic algorithm for constrained hardware- software partitioning

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Genetic algorithm

In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection. Some examples of GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, causal inference, etc.

Memetic algorithm

A memetic algorithm (MA) in computer science and operations research, is an extension of the traditional genetic algorithm (GA) or more general evolutionary algorithm (EA). It may provide a sufficiently good solution to an optimization problem. It uses a suitable heuristic or local search technique to improve the quality of solutions generated by the EA and to reduce the likelihood of premature convergence. Memetic algorithms represent one of the recent growing areas of research in evolutionary computation.

Free software

Free software or libre software or libreware is computer software distributed under terms that allow users to run the software for any purpose as well as to study, change, and distribute it and any adapted versions. Free software is a matter of liberty, not price; all users are legally free to do what they want with their copies of a free software (including profiting from them) regardless of how much is paid to obtain the program.

Free-software license

A free-software license is a notice that grants the recipient of a piece of software extensive rights to modify and redistribute that software. These actions are usually prohibited by copyright law, but the rights-holder (usually the author) of a piece of software can remove these restrictions by accompanying the software with a software license which grants the recipient these rights. Software using such a license is free software (or free and open-source software) as conferred by the copyright holder.

Chromosome (genetic algorithm)

In genetic algorithms (GA), or more general, evolutionary algorithms (EA), a chromosome (also sometimes called a genotype) is a set of parameters which define a proposed solution of the problem that the evolutionary algorithm is trying to solve. The set of all solutions, also called individuals according to the biological model, is known as the population. The genome of an individual consists of one, more rarely of several, chromosomes and corresponds to the genetic representation of the task to be solved.

Open-source software

Open-source software (OSS) is computer software that is released under a license in which the copyright holder grants users the rights to use, study, change, and distribute the software and its source code to anyone and for any purpose. Open-source software may be developed in a collaborative, public manner. Open-source software is a prominent example of open collaboration, meaning any capable user is able to participate online in development, making the number of possible contributors indefinite.

Evolutionary algorithm

In computational intelligence (CI), an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of individuals in a population, and the fitness function determines the quality of the solutions (see also loss function).

Crossover (genetic algorithm)

In genetic algorithms and evolutionary computation, crossover, also called recombination, is a genetic operator used to combine the genetic information of two parents to generate new offspring. It is one way to stochastically generate new solutions from an existing population, and is analogous to the crossover that happens during sexual reproduction in biology. Solutions can also be generated by cloning an existing solution, which is analogous to asexual reproduction. Newly generated solutions may be mutated before being added to the population.

Comparison of free and open-source software licenses

This comparison only covers software licenses which have a linked Wikipedia article for details and which are approved by at least one of the following expert groups: the Free Software Foundation, the Open Source Initiative, the Debian Project and the Fedora Project. For a list of licenses not specifically intended for software, see List of free-content licences. FOSS stands for "Free and Open Source Software". There is no one universally agreed-upon definition of FOSS software and various groups maintain approved lists of licenses.

The Free Software Definition

The Free Software Definition written by Richard Stallman and published by the Free Software Foundation (FSF), defines free software as being software that ensures that the users have freedom in using, studying, sharing and modifying that software. The term "free" is used in the sense of "free speech," not of "free of charge." The earliest-known publication of the definition was in the February 1986 edition of the now-discontinued GNU's Bulletin publication by the FSF.