Questions tagged [evolutionary-computing]
The evolutionary-computing tag has no usage guidance.
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Measuring and maintaining the diversity of individuals in Genetic Algorithm
While I was using the Genetic Algorithm to generate full correct Sudoku grids starting from a population of random grids, I occasionally face the problem of the process being stuck on a local maxima ...
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Genetic algorithm, transformation methods for the different objective function
I am using a genetic algorithm for the optimization of a thermodynamic cycle. The problem has no analytical solution and the solution space is computationally large. The question is the following: How ...
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what does $(1 + (λ, λ))$ Genetic Algorithm mean?
I am discovering the topic of Genetic Algorithms, I read a bit about it on wikipedia and towardsdatascience. When I checked papers some papers, I found them using the notation "$(1 + (λ, λ))$&...
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How to mix populations in multi population genetic algorithm?
I'm working on an optimization problem using genetic algorithm. To increase diversity of potential solutions I'm using multi-population approach: Instead of evolving one population I run 10 ...
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Necessary or useful models/techniques for simulating natural evolution?
I'm a Psychology student with a decent (yet not extensive) knowledge of mathematics and computer science. My knowledge on this two fields are those of a person beginning the third year of computer ...
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Is there any good method to find if a grammar is optimal for a problem?
I've been thinking about grammatical evolution problems and how the grammar influences the algorithm performance. It came to my mind the huge impact that the grammar that you're using has in the time ...
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Repair operator for evolutionary algorithm
I am working on a resource allocation problem using an SPEA 2 evolutionary algorithm. The problem involves decision variables where each variable has a different domain e.g. $E_i \le d_i$ where $E_i$ ...
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Evolutionary optimisation algorithm and graph based search
Simulated annealing and genetic algorithm are examples of evolutionary optimisation algorithms. Both of these methods entail doing a search on a graph of candidate solutions.
Do all other evolutionary ...
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Search techniques to find desired output with complex interdependencies
I am trying to generate output consisting of three-tuples (A,B,C), where A,B, and C are three different datatypes representing different values. I also have a collection of functions $f_i \in F$ ...
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Why Don't We Use Non-ML Artificial Evolution?
I remember reading about Tom Ray's Tierra and how amazing the results it obtained were. However as far as I know, the only "evolution" based computer technology we use now is ML, which is very limited ...
D.W.♦
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Evolutionary algorithm - is there a relation between minimum iterations and size of decision variables
I am solving an optimization problem using SPEA2, my problem has three cases with decision variables 25, 50 and 100 in each case. I want to ask if there is some relationship between the number of ...
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The name for this genetic algorithm variant
What is the name for this variant of genetic algorithm. I'm sure I have read about this in Wikipedia, but now I could not find it:
There in no thing as sequential population. The phenotypes lives and ...
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Comparison of Swarm Intelligence Algorithms with Constraint Violations
I want to compare swarm intelligence algorithms in a optimisation problem. As far as I understand, a typical approach is to perform several runs of each algorithm (say 30 independent runs, with ...
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Is genetic programming relevant today?
My main concern is whether the genetic programming is an active field of research, with some promising applications in practice. It seems like in field of machine learning, the neural networks are the ...
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How to avoid getting stuck on local optimum, for genetic algorithms
I'm programming a genetic algorithm using grammatical evolution. My problem is that I reach local optimal values (premature convergence) and when that happens, I don't know what to do. I'm thinking ...
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Handling eqaulity constraints in genetic algorithms
I am trying to solve an optimization problem with strength pareto algorithm (SPEA2). My decision variable have lower and upper bounds as well as an equality constraint (sum(dp) = 1). I am unable to ...
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Multi objective optimization using genetic algorithm
I have an objective function profit = income - expense . I want to solve it using genetic/evolutionary algorithm (strength pareto SPEA2). Since the algorithm is ...
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Would it ever be possible for computer viruses to evolve new "genes" to allow them to perform their job?
As an A-level Biology student, I have thought a lot about the links with Biology and Computer Science, and something that often comes to mind are the links between Immunology and Computer Security/...
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Difference between Memetic and Cultural algorithms
What is the difference between a memetic algorithm and a cultural algorithm? I mean they're both evolutionary algorithms where they select a subset of the population to apply some local search logic. ...
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Does local optimization in a genetic algorithm decrease diversity?
I want to create a hybrid genetic algorithm for a project to solve really high dimensional problems (1000+) One of my ideas is to incorporate a local optimization method within GA so each individual ...
CommunityBot
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Variation of rank selection in genetic algorithm
I'm looking for a specific variation of rank selection in genetic algorithms.
I came across a python program tailored for a specific problem that uses a variant of "rank" selection. In normal rank ...
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Data structure for storing edges of a graph
I'm currently working on my masters thesis, and it's about clustering on graphs. I'm working with an idea using ants to solve the problem. I'm currently working on the implementation and am wondering ...
CommunityBot
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Can the reproduction function of an evolutionary algorithm consider gene strength?
I am trying to solve the Zen Garden puzzle using an evolutionary algorithm. My question relates to evolutionary algorithms in general.
Bit about evolutionary algorithms:
An evolutionary algorithm is ...
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Gramatical evolution doesn't result on creating good constants
I'm using Grammatical Evolution for symbolic regression tasks (i.e. searching the space of mathematical expressions to find the model that best fits a given dataset).
I'm evolving solutions according ...
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Mutation and crossover operations in discrete differential evolutionary operations?
I need to use discrete differential evolutionary algorithm for assigning discrete values from set size $L$ to vectors of size $D$ where $L$ could be smaller, equal or larger than $D$. Elements of ...
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Evolutionary algorithm in stochastic environment
Consider the following model problem:
I want to use an evolutionary algorithm to optimize the starting point of particles for which it is apriori clear where they would start in state space, but not ...
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How do I stop "cheating" in reinforcement learning (MLP+Evo. Algorithm)?
I have a two hidden-layer MLP. I am trying to teach it classification of the sine function. For instance, if there is an [x,y] point above the sine function, the ANN should classify that point as a 1. ...
D.W.♦
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Is Differential Evolution a genetic algorithm?
I am trying to classify the Differential Evolution algorithm according to the framework in the book:
Introduction to Evolutionary Computing
The authors classify the field of evolutionary ...
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Is there any example of automatas (or similar) systems that emerge complex internal structures on its own?
Automatas are turing-complete grid-based systems with progression rules on which we can encode arbitrarily complex structures. For example, this is a "glider gun" on Conway's Game of Life:
Due to ...
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Is there a research name for "systems that steadily grow in complexity as they are computed"?
I have an intuitive concept of systems that grows in complexity steadily as it computes. I can think in some examples:
Nature. Given the physical laws, some initial conditions (say, the Earth planet ...
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A clarification on the taxonomy of Evolutionary Algorithms
A rather basic question but I am confused about the characterization of a certain local search method which I want to describe in the framework of EAs. In particular, consider an EA which in every ...
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What makes a metaheuristic meta?
According to Wikipedia:
...metaheuristic is a higher-level procedure or heuristic designed to
find, generate, or select a lower-level procedure or heuristic
(partial search algorithm) that may ...
CommunityBot
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Are there some real-world optimization problems with very cheap objective functions?
Many real world optimization tasks (especially black box optimization) have objective functions, which are quite expensive to evaluate. For example to find the optimal shape of an airplane wing, a ...
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Are genetic algorithms special instances of random search done in an unexpectedly short run-time? [closed]
I was wondering since randomness is embedded in genetic algorithms at almost every level, is there a really fine line between genetic algorithms and pure random search?
Ever since I finished my ...
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Time Complexity of Genetic Algorithms
How do you determine the Time Complexity of a Genetic Algorithm(in general)? If possible.
I have been thinking about this a lot, and all of the teaching I have had is related to determining the Time ...
CommunityBot
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What does this performance formula mean?
I have to make a quick clustering program but the following formula is gibberish to me:
$\operatorname{Perf}(X,C) = \sum\limits_{i=1}^n\min\{||X_i-C_l||^2 \mid l = 1,...,K\}$
where $X$ is a ...
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Why has research on genetic algorithms slowed?
While discussing some intro level topics today, including the use of genetic algorithms; I was told that research has really slowed in this field. The reason given was that most people are focusing on ...
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