26 papers · ranked by Valyu relevance
Tomasz Tarkowski
The idea of application of biological evolution [1] and genetic [2] principles to the optimization problems was first sketched by Alan Turing in his 1948 essay titled Intelligent Machinery [3] and later extended by himself [4] to a technique which is now called genetic programming [5]. These works were the very…
Okezue Bell
In recent years, optimization problems have become increasingly more prevalent due to the need for more powerful computational methods. With the more recent advent of technology such as artificial intelligence, new metaheuristics are needed that enhance the capabilities of classical algorithms. More recently…
He Li, Naiyu Shi
In order to address the application of genetic optimization algorithms to financial investment portfolio issues, the optimal allocation rate must be high and the risk is low. This paper uses quadratic programming algorithms and genetic algorithms as well as quadratic programming algorithms, Matlab planning solutions…
Jonas Verhellen
Computer-assisted design of small molecules has experienced a resurgence in academic and indus- trial interest due to the widespread use of data-driven techniques such as deep generative models. While the ability to generate molecules that fulfill required chemical properties is encouraging, the use of deep learning…
Brianna Greenstein, Danielle Elsey, Geoffrey Hutchison
Genetic algorithms (GAs) are a powerful tool to search large chemical spaces for inverse molecular design. However, GAs have multiple hyperparameters that have not been thoroughly investigated for chemical space searches. In this work, we examine the general effects of a number of hyperparameters, such as population…
Leo Sünkel, Darya Martyniuk, Denny Mattern, Johannes Jung + 1 more
'Adrian Paschke'] The design of quantum circuits is often still done manually, for instance by following certain patterns or rule of thumb. While this approach may work well for some problems, it can be a tedious task and present quite the challenge in other situations. Designing the architecture of a circuit for a…
Zachary Jones, Mohammad A. Alsaad, Ankush Vavishta
QWOP is a browser-based, 2-dimensional flash game in which the player controls an Olympic sprinter competing in a simulated 100-meter race. The goal of the game is to advance the runner to the end of the 100-meter race as quickly as possible using the 'Q', 'W', 'O', and 'P' keys, which control the muscles in the…
Junyu Zhang, Pengyuan Qi, Jike Wang, S. Svensson
A universal optimization simulation method based on a multi-objective genetic algorithm is introduced; this is the first attempt to optimize the elements of a beamline using this method.
Kara Layne Johnson, Nicole Bohme Carnegie
Genetic algorithms mimic the process of natural selection in order to solve optimization problems with minimal assumptions and perform well when the objective function has local optima on the search space. These algorithms treat potential solutions to the optimization problem as chromosomes, consisting of genes which…
Gemma Douilhet, Mahesan Niranjan, Andres Vallejo, Kalum Clayton + 5 more
The ability to reliably predict and infer cellular responses to environmental exposures would offer a major advance in the investigation of immune regulation in health and disease. One possible approach is the use of in silico modelling. Design of such a mathematical kinetic model would be based on existing knowledge…
Zenghua Chen, Lingjian Zhu, He Lu, Shichao Chen + 4 more
'Sheng Liu' 'Yunjun Han' 'Gang Xiong'] Health monitoring and fault diagnosis of rolling bearings are crucial for the continuous and effective operation of mechanical equipment. In order to improve the accuracy of BP neural network in fault diagnosis of rolling bearings, a feature model is established from the vibration…
Alireza Rezaee
This paper presents a genetic algorithm (GA) approach to cost-optimal task scheduling in a production line. The system consists of a set of serial processing tasks, each with a given duration, unit execution cost, and precedence constraints, which must be assigned to an unlimited number of stations subject to a…
Daekyung Lee, Beom Jun Kim
We propose an extended genetic algorithm (GA) with different local environmental conditions. Genetic entities, or configurations, are put on nodes in a ring structure, and location-dependent environmental conditions are applied for each entity. Our GA is motivated by the geographic aspect of natural evolution…
Ahmed Redha Mahlous, Houssam Mahlous, Yilun Shang
Universities face a constant challenge when distributing students and allocating them to their required classes, especially for a large mass of students. Generating feasible timetables is a strenuous task that requires plenty of resources, which makes it impractical to take student preferences into consideration during…
Kathleen S. Dreyer, Anh V. Nguyen, Gauri G. Bora, Lauren E. Redus + 6 more
Genetic programs can direct living systems to perform diverse, pre-specified functions. As the library of parts available for building such programs continues to expand, computation-guided design is increasingly helpful and necessary. Predictive models aid the challenging design process, but iterative simulation and…
Ricardo Medel-Esquivel, Isidro Gómez-Vargas, Alejandro A. Morales Sánchez, Ricardo García‐Salcedo + 1 more
'Alejandro A. Morales Sánchez' 'Ricardo García‐Salcedo' 'J. Alberto Vázquez'] Genetic algorithms are a powerful tool in optimization for single and multi-modal functions. This paper provides an overview of their fundamentals with some analytical examples. In addition, we explore how they can be used as a parameter…
Authors not listed
Finding the most stable adsorption geometry of a flexible molecule on a catalytic surface remains a key challenge due to the high dimensionality and ruggedness of the potential energy surface. We present a Gradient-Enhanced Genetic Algorithm (GE-GA) for the global optimization of adsorbate–surface configurations…
Justin Villard, Murat Kılıç, Ursula Rothlisberger
Identification of the most stable structure(s) of a system is a prerequisite for the calculation of any of its properties from first-principles. However, even for relatively small molecules, exhaustive explorations of the potential energy surface (PES) are severely hampered by the dimensionality bottleneck. In this…
Sizhe Yuen, Thomas H. G. Ezard, Adam J. Sobey
Evolutionary computation is a group of biologically inspired algorithms used to solve complex optimization problems. It can be split into evolutionary algorithms, which take inspiration from genetic inheritance, and swarm intelligence algorithms, that take inspiration from cultural inheritance. However, much of the…
Authors not listed
Genetic Algorithms are a powerful method to solve optimization problems with complex cost functions over vast search spaces that rely in particular on recombining parts of previous solutions. Crossover operators play a crucial role in this context. Here, we describe a large class of these operators designed for…
Y. Ma, Tan Chye Cheah
problem Authors: ['Y. Ma' 'Tan Chye Cheah'] This paper implements a new way of solving a problem called the traveling salesman problem (TSP) using quantum genetic algorithm (QGA). We compared how well this new approach works to the traditional method known as a classical genetic algorithm (CGA). The TSP is a…
Eden Tian Hwa Ng, Akira R. Kinjo
Plasticity-led evolution (PLE), where evolution is initiated by the environmental induction of novel adaptive phenotypes, which is followed by genetic accommodation, has been proposed to remedy the difficulties of mutation-led evolution (MLE) implied by the standard evolutionary theory, according to which evolution is…
Alexander Lalejini, Emily Dolson, Anya E. Vostinar, Luis Zaman
Directed microbial evolution harnesses evolutionary processes in the laboratory to construct microorganisms with enhanced or novel functional traits. Attempting to direct evolutionary processes for applied goals is fundamental to evolutionary computation, which harnesses the principles of Darwinian evolution as a…
Azadeh Hassanpour, Antje Rohde, Henner Simianer, Torsten Pook
Plant breeding is a complex process that involves trade-offs among competing breeding objectives and limited resources. Despite the necessity for optimization of breeding program design, the inherent complexity can make optimization challenging. Most often, a predefined set of scenarios is compared or a single…
Kosuke Hamazaki, Hiroyoshi Iwata
Emerging technologies such as genomic selection have been applied to modern plant and animal breeding to increase the speed and efficiency of variety release. However, breeding requires decisions regarding parent selection and mating pairs, which significantly impact the ultimate genetic gain of a breeding scheme. The…
Anastassiya Perfilyeva, Rustam Mussabayev, Kira Bespalova, Yelena Kuzovleva + 8 more
The breed conformity evaluation is crucial for the preservation of the traits that characterise each dog breed. The use of genetic markers for this purpose provides a precision and objectivity that can surpass the reliability of phenotypic evaluations. In this study, we present a new simple algorithm for assessing…