Genetic algorithms are a randomized search method based on the biological model of evolution through mating and mutation. In the classic genetic algorithm, problem solutions are encoded into bit strings which are tested for fitness, then the best bit strings are combined to form new solutions using methods which mimic the Darwinian process of "survival of the fittest" and the exchange of DNA which occurs during mating in biological systems. The programming of genetic algorithms involves little more than bit manipulation and scoring the quality of solutions. Genetic algorithms have been applied to problems as diverse as graph partitioning and the automatic creation of programs to match mathematical functions.
Genetic algorithms are a randomized search method which "breeds" effective solutions to problems through simulation of Darwinian Evolution. Large numbers of potential solutions are created at random. The solutions which show the most promise are then breed together to produce new solutions which receive most of their 'genetic stock' from the better solutions in the previous generation. This is similar to the "survival of the fittest" shown in biological systems, where the individuals which are best adapted to their environment breed more offspring, resulting in the better adapted genetic material carrying forward into future generations.
The history of genetic algorithms is most commonly traced to Holland's text "Adaptation in Natural and Artificial Systems", published in 1975. Earlier works by Holland and others shows that the concept of genetic algorithms first began to form in the late 1960s . Around that time, Bagley first coined the phrase "genetic algorithm" in his dissertation. Holland...
... middle of paper ...
...Come of Age, David E. Goldberg, Communications of the ACM, March 1994, pp 113-119.
 Genetic Algorithms: A Survey, M. Srinivas, Latit M. Patnaik, IEEE Computer, June 1994, pp 17-26.
 Genetic Algorithm and Graph Partitioning, Thang Nguyen Bui, Byung Ro Moon, IEEE Transactions on Computers, July 1996, pp 841-855.
 Genetic Programming: A Paradigm for Genetically Breeding Populations of Computer Programs to Solve Problems, John R. Koza, Stanford Technical Report STAN-CS-90-1314, June 1990. Available at ftp://elib.stanford.edu/pub/reports/cs/tr/90/1314/. This material is also discussed in Koza's text "Genetic Programming: On the Programming of Computers by Means of Natural Selection".
Need Writing Help?
Get feedback on grammar, clarity, concision and logic instantly.Check your paper »
- Abstract Genetic algorithms are a randomized search method based on the biological model of evolution through mating and mutation. In the classic genetic algorithm, problem solutions are encoded into bit strings which are tested for fitness, then the best bit strings are combined to form new solutions using methods which mimic the Darwinian process of "survival of the fittest" and the exchange of DNA which occurs during mating in biological systems. The programming of genetic algorithms involves little more than bit manipulation and scoring the quality of solutions.... [tags: Biology Genetics]
1831 words (5.2 pages)
- Selecting appropriate weighting matrices for desired Linear Quadratic Regulator (LQR) controller design using evolutionary algorithms is presented in this paper. Obviously, it is not easy to determine the appropriate weighting matrices for an optimal control system and a suitable systematic method is not presented for this goal. In other words, there isn’t direct relationship between weighting matrices and control system characteristics and selecting these matrices is done using by trial and error based on designer’s experience.... [tags: Mathematics]
2475 words (7.1 pages)
- Decision Tree Analysis In data mining, the decision tree analysis is used to determine the best choice from various possible options. Through this process, researchers and managers get an opportunity to evaluate the risks, benefits and inconsistencies associated with the decisions. The first step is structuring the problems or issues being faced by the organization as a tree. At the end of each branch, all the benefits are listed to help in evaluating the path with the most benefits. After the benefits have been determined, the next step involves assigning subjective probabilities to all the activities on the tree (Qu, Adam, Yasui, Ward, & Cazares, 2002).... [tags: Data Mining]
577 words (1.6 pages)
- Optimization, in simple terms, means minimize the cost incurred and maximize the profit such as resource utilization. EAs are population based metaheuristic (means optimize problem by iteratively trying to improve the solution with regards to given measure of quality) optimization algorithms that often perform well on approximating solution to all types of problem because they do not make any assumptions about the underlying evaluation of fitness function. There are many EAs available viz. Genetic Algorithm (GA)  , Artificial Immune Algorithm (AIA) , Ant Colony Optimization (ACO) , Particle Swarm Optimization (PSO) , Differential Evolution (DE) [5, 6], Harmony Search (HS) , Ba... [tags: Application, System, Implementation]
900 words (2.6 pages)
- ... This approach is known as rigid-body docking . It depends from case to case, whether this approximation is accurate enough or not. If there are significant conformational changes within the molecules during the complex formation, this approach is inadequate. However, generation and scoring of all possible conformations is prohibitively expensive in computer time. Flexible docking algorithms  must therefore take into consideration only a selected subset of possible conformational changes.... [tags: structure, ligand, algorithms]
935 words (2.7 pages)
- Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Previously, a number of statistical algorithms had been applied to perform clustering to the data including the text documents. There are recent endeavors to enhance the performance of the clustering with the optimization based algorithms such as the evolutionary algorithms. Thus, document clustering with evolutionary algorithms became an emerging topic that gained more attention in the recent years.... [tags: clustering, inspection, research]
742 words (2.1 pages)
- The coming of the most recent generations of sequencing technologies  has opened a lot of new research chances in the fields of science (biology) and medication, including cell Deoxyribonucleic Acid (DNA) sequencing, gene disclosure and evolutionary connections. These sophisticated technologies have helped the exponential development of biological information that is accessible for specialists. For example, the Genbank  has multiplied its information measure at regular intervals (approximately 18 months) and in its latest release of February 2014 it included over 158 × 109 base pairs (bps) from a few distinctive species.... [tags: algorithms, genetics, programming ]
809 words (2.3 pages)
- The healthcare industry has come a long way in terms of technological advances. These advances have had significant benefits in diagnosis, treatment, and the way medicine is practiced today. Unfortunately, these technological advances also come with ethical issues and dilemmas the healthcare professionals must face. Genetic testing is an area that has had significant advancement over the past few years. Genetic testing can provide important information regarding diagnosis, treatment, and prevention of illness or disease (Mayo Clinic, 2015).... [tags: Health care, Health care provider, Medicine]
1093 words (3.1 pages)
- Increasing complexities in industrial processes have compelled the control engineers to implement advanced control strategies to improve the efficiency of the process control system. Usage of PID controllers has become indispensible for its simplicity, reliability and flexibility . The proportional term in the controller generally helps in establishing system stability and improving the transient response while the derivative term is often used when it is necessary to improve the closed loop response speed even further.... [tags: PID controller, ZN method, mutation]
1300 words (3.7 pages)
- Before targeedt genome engineering emerged there was classical plant breeding and transgenic methods to modify crop plants, and ensure sustainable production. Researchers today have utilized methods like zinc finger nucleases (ZNF) and TAL effector nucleases (TALENs) to create these improved crop plants. Recently, a new method has caught the eye of many researchers; a method that simplifies the process and saves labor: CRISPR-Cas9 system. This method of genome engineering is particularly interesting not only for researchers but also for millions of Americans.... [tags: CRISPR-Cas9, genome engineering, plants]
917 words (2.6 pages)