zoli801

zoli801 / Data-Fusion-Contest-2026---3-

Public

решение для Задача 3 "Герои"

15
0
100% credibility
Found Mar 03, 2026 at 15 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Jupyter Notebook
AI Summary

This project shares a winning strategy guide for the 'Heroes' task in the Data Fusion Contest 2026, helping optimize hero routes to collect maximum gold while respecting time windows, costs, and movement points.

How It Works

1
🏆 Discover the Heroes Challenge

You stumble upon the fun Data Fusion Contest where you hire heroes to collect gold by visiting special objects around the map.

2
📖 Explore the Top Strategy Guide

You read a clever plan that shows how to send heroes to the best spots without wasting time or money.

3
🦸‍♂️ Hire Smart Heroes

You pick heroes one by one, choosing those who bring back more treasure than they cost to hire.

4
🚶‍♂️ Map Out Quick Paths

You guide each hero to the closest reachable objects first, saving energy for bigger adventures later.

5
⏰ Watch the Clock

You ensure heroes only visit during open hours and carry over leftover energy to the next day.

💰 Win Big with Max Gold!

Your heroes collect the most treasure ever, putting you at the top of the leaderboard with huge rewards.

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AI-Generated Review

What is Data-Fusion-Contest-2026---3-?

This Jupyter Notebook delivers a complete solution for Task 3 "Heroes" in the Data Fusion Contest 2026, tackling the challenge of assigning heroes to visit time-sensitive objects while juggling hiring costs, movement points, and daily carryover. It optimizes routes using greedy nearest-neighbor logic to maximize rewards under strict constraints like visit costs and open windows. Run it on contest data to generate high-scoring submissions that respect all rules.

Why is it gaining traction?

It stands out by nailing contest-specific tricks, like prioritizing expiring objects and squeezing efficiency from leftover points, outperforming naive approaches without overcomplicating inputs. Developers grab it for the plug-and-play notebook that scales to thousands of objects and heroes, plus a Kaggle-linked top score that proves real-world punch. No setup hassle—just load data and iterate.

Who should use this?

Data contest competitors prepping for Data Fusion 2026 events needing a baseline for hero-assignment puzzles. Optimization enthusiasts adapting it to logistics routing or resource scheduling in games/simulations. Teams short on time for greedy algorithms with time windows.

Verdict

Grab it if you're in the contest ecosystem—15 stars and solid Kaggle win make it a quick win for benchmarking, despite the 1.0% credibility score signaling early-stage maturity and thin docs. Skip for production unless you fork and harden it.

(178 words)

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