Armando B. Mendes » otimização

Optimal Wordle Solutions

Posted by Armando Brito Mendes | Filed under Investigação Operacional, materiais para profissionais

Uma aplicação que utiliza um processo de pesquisa em árvore para resolver o jogo wordle

The game Wordle has a lot of speculation online about what is the “best” first word. If we are exploring optimal strategies to solve the original game in the least number of guesses, most of it is wrong.

For humans, almost all of these words are great! However for optimal strategies, we need to examine all of the guesses, not just the first word. It turns out, it’s possible to solve 99% of all puzzles in only 4 guesses or with an average of ~3.42 guesses per win, but not with most of the “best” words found online.

Try out my solver with the best strategies that have been found so far.

Jonathan Olson

Tags: jogo, otimização

Read more | Comments off | January 25th, 2022

Map of Best Breweries in America

Posted by Armando Brito Mendes | Filed under Investigação Operacional, mapas SIG's, visualização

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Um mapa com as melhores produtoras de cerveja artesanal nos EUA e uma rota otimizada com algoritmos genéticos

RateBeer puts out a list every year for top 100 breweries in the world. The rankings are based on reviews, range across styles, and historical performance (and maybe a bit of subjectivity). RateBeer just published the list for 2018. Here’s a map of the 73 U.S.-based breweries.

Brewery Road Trip, Optimized With Genetic Algorithm

Now that we know where they are, let’s find out how to visit all of them in one go.

Tags: belo, grafos, mapas, otimização, R-software, SIG

Read more | Comments off | April 5th, 2019

Extracting Seasonality and Trend from Data: Decomposition Using R

Posted by Armando Brito Mendes | Filed under estatística, Investigação Operacional, lições, linguagens de programação, materiais ensino, materiais para profissionais

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Uma excelente descrição da decomposição clássica com Python e R.

Time series decomposition works by splitting a time series into three components: seasonality, trends and random fluctiation. To show how this works, we will study the decompose( ) and STL( ) functions in the R language.

Understanding Decomposition

Decompose One Time Series into Multiple Series

Time series decomposition is a mathematical procedure which transforms a time series into multiple different time series. The original time series is often split into 3 component series:

Seasonal: Patterns that repeat with a fixed period of time. For example, a website might receive more visits during weekends; this would produce data with a seasonality of 7 days.
Trend: The underlying trend of the metrics. A website increasing in popularity should show a general trend that goes up.
Random: Also call “noise”, “irregular” or “remainder,” this is the residuals of the original time series after the seasonal and trend series are removed.

Tags: engenharia, inferência, otimização, previsão

Read more | Comments off | January 22nd, 2019

Voronoi diagram from smooshing paint between glass

Posted by Armando Brito Mendes | Filed under Investigação Operacional, mapas SIG's, matemática, videos

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Uma abordagem original aos diagramas de Voronoi.

Tags: belo, otimização

Read more | Comments off | January 11th, 2019

Data Analysis Method: Mathematics Optimization to Build Decision Making

Posted by Armando Brito Mendes | Filed under Investigação Operacional, matemática, SAD - DSS

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Uma pequena introdução à utilização de otimização na análise de dados

Optimization is a problem associated with the best decision that is effective and efficient decisions whether it is worth maximum or minimum by way of determining a satisfactory solution.

Optimization is not a new science. It has grown even since Newton in the 17th century discovered how to count roots. Currently the science of optimization is still evolving in terms of techniques and applications. Many cases or problems in everyday life that involve optimization to solve them. Lately much developed especially in the emergence of new techniques to solve the problem of optimization. To mention some, among others, conic programming, semi definite programming, semi infinite programming and some meta heuristic techniques.

Tags: análise de dados, data mining, otimização

Read more | Comments off | January 3rd, 2018

Markov Chains explained visually

Posted by Armando Brito Mendes | Filed under Investigação Operacional, matemática, materiais ensino, visualização

Boa forma de perceber como funcionam as cadeias de Markov

Adding on to their series of graphics to explain statistical concepts, Victor Powell and Lewis Lehe use a set of interactives to describe Markov Chains. Even if you already know what Markov Chains are or use them regularly, you can use the full-screen version to enter your own set of transition probabilities. Then let the simulation run.

Tags: grafos, otimização

Read more | Comments off | August 12th, 2014