Hey y'all! 👋
Hope everybody is having a fantastic Friday and that you all have wonderful weekends!
Looking back on this past week, what was something you were proud of accomplishing?
All wins count — big or small 🎉
Examples of 'wins' include:
- Starting a new project
- Fixing a tricky bug
- Going to a concert 🎸
Everybody have a good one!
Latest comments (33)
Migrated my hobby project from heroku to render
Cleared a dozen tasks off my to-do list.
My blog redesign finally reached a satisfying stage: roneo.org/en
And I published two new articles out there, and my first post on dev.to.
:proud:
Fixed a tricky race condition refreshing a jwt. 🙌
Finished ten weeks from this 22 weeks JavaScript Bootcamp & the first course from Advanced full stack web development
We published a full tuto/storytelling about Neo4J Bloom
📘 Neo4J Bloom : Install & Storytell 🎞️
adriens for opt-nc ・ Sep 5 ・ 1 min read
And prepared stuff to announce some open source stuff for next week <3
This week i started to swin again. This may not be related to dev, but makes my body function way better and that relates a lot to the way i develop my projects. This week i found some annoying bugs at work, finished some projects at work and reinstalled my rpi.
Oooo that's a great one. I really wanna start back swimming too. It just makes me feel better all over + makes me sleep better.
A Java library I develop, Chips-n-Salsa, for evolutionary algorithms and self-adaptive local search, was mentioned in the awesome list, Awesome Machine Learning.
GitHub repository at:
A Java library of Customizable, Hybridizable, Iterative, Parallel, Stochastic, and Self-Adaptive Local Search Algorithms
Chips-n-Salsa
Copyright (C) 2002-2022 Vincent A. Cicirello.
Website: chips-n-salsa.cicirello.org/
API documentation: chips-n-salsa.cicirello.org/api/
How to Cite
If you use this library in your research, please cite the following paper:
Overview
Chips-n-Salsa is a Java library of customizable, hybridizable, iterative, parallel, stochastic, and self-adaptive local search algorithms. The library includes implementations of several stochastic local search algorithms, including simulated annealing, hill climbers, as well as constructive search algorithms such as stochastic sampling. Chips-n-Salsa now also includes genetic algorithms as well as evolutionary algorithms more generally. The library very extensively supports simulated annealing. It includes several classes for representing solutions to a variety of optimization problems. For…
Website at:
Chips-n-Salsa - A Java library of customizable, hybridizable, iterative, parallel, stochastic, and self-adaptive local search algorithms
The Chips-n-Salsa library includes implementations of several stochastic local search algorithms, including simulated annealing, hill climbers, as well as constructive search algorithms such as stochastic sampling; and now also includes genetic algorithms as well as evolutionary algorithms more generally. It includes several classes for representing solutions to a variety of optimization problems. For example, the library includes a BitVector class that implements vectors of bits, as well as classes for representing solutions to problems where we are searching for an optimal vector of integers or reals. For each of the built-in representations, the library provides the most common mutation operators and crossover operators for use with evolutionary algorithms. The library provides extensive support for permutation optimization problems, including implementations of many different mutation operators for permutations, and utilizing the efficiently implemented Permutation class of the JavaPermutationTools (JPT) library. Chips-n-Salsa is customizable, making extensive use of generic types, enabling using the library to optimize other types of representations beyond what is provided in the library. It is hybridizable, providing support for integrating multiple forms of local search (e.g., using a hill climber on a solution generated by simulated annealing), creating hybrid mutation operators (e.g., local search using multiple mutation operators), and classes that support running more than one type of search for the same problem concurrently using multiple threads as a form of algorithm portfolio. Chips-n-Salsa is iterative, with support for multistart metaheuristics, including implementations of several restart schedules for varying the run lengths across the restarts. It also supports parallel execution of multiple instances of the same, or different, stochastic local search algorithms for an instance of a problem to accelerate the search process. The library supports self-adaptive search in a variety of ways, such as including implementations of adaptive annealing schedules for simulated annealing, such as the Modified Lam schedule, implementations of the simpler annealing schedules but which self-tune the initial temperature and other parameters, and restart schedules that adapt to run length.
First of all congratulations! 😁
I'm wondering how you choose the name though 😂 looking at it makes sense now but the process of choosing it must've been quite interesting
It was like a puzzle. I started by writing down words and phrases that were relevant to the library. And then rearranged them until I found something that made sense.
I went back to an old personal project, for turning images into .ico files, and wrote a method to do that. Previously I had been stumped because .NET only allows reading .ico files and note writing them. It wasn't nearly as hard as I thought it would be.
my humble workspace
Features:
I'm confident that this setup went to a big bunch of iterations 😁
Checking the details it's one of those where you can sit for hours and still having all you need at reach ain't it?
Yup. I should put a badminton racket to demonstrate that.
Woaaa that looks awesomely comfortable. Nice feature list too. Oh so cozy!! 😌
Also, the optional sword holster! lol! ⚔️