Journal ArticleDOI
Genetic algorithms: a survey
M. Srinivas,Lalit M. Patnaik +1 more
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TLDR
The analogy between genetic algorithms and the search processes in nature is drawn and the genetic algorithm that Holland introduced in 1975 and the workings of GAs are described and surveyed.Abstract:
Genetic algorithms provide an alternative to traditional optimization techniques by using directed random searches to locate optimal solutions in complex landscapes. We introduce the art and science of genetic algorithms and survey current issues in GA theory and practice. We do not present a detailed study, instead, we offer a quick guide into the labyrinth of GA research. First, we draw the analogy between genetic algorithms and the search processes in nature. Then we describe the genetic algorithm that Holland introduced in 1975 and the workings of GAs. After a survey of techniques proposed as improvements to Holland's GA and of some radically different approaches, we survey the advances in GA theory related to modeling, dynamics, and deception. >read more
Citations
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Journal ArticleDOI
A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems
Tracy D. Braun,Howard Jay Siegel,N.B. Beck,Ladislau Bölöni,Muthucumaru Maheswaran,Albert Reuther,James Patrick Robertson,Mitchell D. Theys,Bin Yao,Debra Hensgen,Richard F. Freund +10 more
TL;DR: It is shown that for the cases studied here, the relatively simple Min?min heuristic performs well in comparison to the other techniques, and one even basis for comparison and insights into circumstances where one technique will out-perform another.
Journal ArticleDOI
Static scheduling algorithms for allocating directed task graphs to multiprocessors
Yu-Kwong Kwok,Ishfaq Ahmad +1 more
TL;DR: A taxonomy that classifies 27 scheduling algorithms and their functionalities into different categories is proposed, with each algorithm explained through an easy-to-understand description followed by an illustrative example to demonstrate its operation.
Journal ArticleDOI
Search‐based software test data generation: a survey
TL;DR: Some of the work undertaken in the use of metaheuristic search techniques for the automatic generation of test data is surveyed, discussing possible new future directions of research for each of its different individual areas.
Journal ArticleDOI
Genetic algorithms: concepts and applications [in engineering design]
Kim F. Man,Ke Tang,Sam Kwong +2 more
TL;DR: In this article, the authors introduce genetic algorithms (GA) as a complete entity, in which knowledge of this emerging technology can be integrated together to form the framework of a design tool for industrial engineers.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.