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The overall aim of the software industry is to ensure delivery of high quality software to the end user. To ensure high quality software, it is required to test software. Testing ensures that software meets user specifications and…

Software Engineering · Computer Science 2014-11-06 Chayanika Sharma , Sangeeta Sabharwal , Ritu Sibal

This manuscript contains an outline of lectures course "Evolutionary Algorithms" read by the author. The course covers Canonic Genetic Algorithm and various other genetic algorithms as well as evolutionary strategies, genetic programming,…

Neural and Evolutionary Computing · Computer Science 2022-03-31 Anton V. Eremeev

The talk describes a general approach of a genetic algorithm for multiple objective optimization problems. A particular dominance relation between the individuals of the population is used to define a fitness operator, enabling the genetic…

Artificial Intelligence · Computer Science 2008-09-03 Martin Josef Geiger

In the context of evolutionary quantum computing in the literal meaning, a quantum crossover operation has not been introduced so far. Here, we introduce a novel quantum genetic algorithm which has a quantum crossover procedure performing…

Neural and Evolutionary Computing · Computer Science 2014-02-05 Akira SaiToh , Robabeh Rahimi , Mikio Nakahara

We investigate the ability of a genetic algorithm to design cellular automata that perform computations. The computational strategies of the resulting cellular automata can be understood using a framework in which ``particles'' embedded in…

adap-org · Physics 2015-06-30 James P. Crutchfield , Melanie Mitchell , Rajarshi Das

Partial search has been proposed recently for finding the target block containing a target element with fewer queries than the full Grover search algorithm which can locate the target precisely. Since such partial searches will likely be…

Quantum Physics · Physics 2010-05-24 Byung-Soo Choi , Thomas A. Walker , Samuel L. Braunstein

This paper presents a new type of genetic algorithm for the set covering problem. It differs from previous evolutionary approaches first because it is an indirect algorithm, i.e. the actual solutions are found by an external decoder…

Neural and Evolutionary Computing · Computer Science 2010-07-05 Uwe Aickelin

This paper explores the use of genetic algorithms for the design of networks, where the demands on the network fluctuate in time. For varying network constraints, we find the best network using the standard genetic algorithm operators such…

Neural and Evolutionary Computing · Computer Science 2009-11-10 Matthew J. Berryman , Andrew Allison , Derek Abbott

We present a genetic algorithm which is distributed in two novel ways: along genotype and temporal axes. Our algorithm first distributes, for every member of the population, a subset of the genotype to each network node, rather than a…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Minkyu Kim , Varun Aggarwal , Una-May O'Reilly , Muriel Medard

Functions of chemical composition are complex and discrete in nature making it impossible to optimize them with gradient methods. Genetic algorithms, which do not use derivative information, are used to maximize the thermal conductivity of…

Materials Science · Physics 2018-01-30 Alexander Kerr , Kieran Mullen

This thesis investigates the use of problem-specific knowledge to enhance a genetic algorithm approach to multiple-choice optimisation problems.It shows that such information can significantly enhance performance, but that the choice of…

Neural and Evolutionary Computing · Computer Science 2010-07-05 Uwe Aickelin

The choice of crossover and mutation strategies plays a crucial role in the searchability, convergence efficiency and precision of genetic algorithms. In this paper, a novel improved genetic algorithm is proposed by improving the crossover…

Neural and Evolutionary Computing · Computer Science 2022-10-12 Dingming Yang , Zeyu Yu , Hongqiang Yuan , Yanrong Cui

This paper presents the coupling of a building thermal simulation code with genetic algorithms (GAs). GAs are randomized search algorithms that are based on the mechanisms of natural selection and genetics. We show that this coupling allows…

Neural and Evolutionary Computing · Computer Science 2012-12-24 Alfred Jean Philippe Lauret , Harry Boyer , Carine Riviere , Alain Bastide

Genetic algorithms are a well-known method for tackling the problem of variable selection. As they are non-parametric and can use a large variety of fitness functions, they are well-suited as a variable selection wrapper that can be applied…

Machine Learning · Statistics 2016-04-25 Chee Chun Gan , Gerard Learmonth

Genetic Regulatory Networks (GRNs) plays a vital role in the understanding of complex biological processes. Modeling GRNs is significantly important in order to reveal fundamental cellular processes, examine gene functions and understanding…

Computational Engineering, Finance, and Science · Computer Science 2012-05-10 Khalid Raza , Rafat Parveen

This work was inspired by author experiences with a telescope scheduling. Author long time goal is to develop and further extend software for an autonomous observatory. The software shall provide users with all the facilities they need to…

Artificial Intelligence · Computer Science 2010-02-02 Petr Kubanek

Viruses utilize various means to circumvent the immune detection in the biological systems. Several mathematical models have been investigated for the description of viral dynamics in the biological system of human and various other…

Information Retrieval · Computer Science 2009-12-14 Jayanthi Manicassamy , P. Dhavachelvan

The task of olfactory search is ubiquitous in nature and in technology, from animals in the quest of food or of a mating partner, to robots searching for the source of hazardous fumes in a chemical plant. Here, we focus on the algorithmic…

Biological Physics · Physics 2024-05-07 Antonio Celani , Emanuele Panizon

A quantum algorithm for general combinatorial search that uses the underlying structure of the search space to increase the probability of finding a solution is presented. This algorithm shows how coherent quantum systems can be matched to…

Quantum Physics · Physics 2009-10-30 Tad Hogg

The paper presents a comprehensive performance evaluation of some heuristic search algorithms in the context of autonomous systems and robotics. The objective of the study is to evaluate and compare the performance of different search…

Multiagent Systems · Computer Science 2023-10-05 Aya Kherrour , Marco Robol , Marco Roveri , Paolo Giorgini