facility-location-problem
CommunityOptimize facility placement for cost savings.
Data & Analytics#optimization#logistics#network design#operations research#site selection#facility location
Authorkishorkukreja
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps determine the optimal locations for facilities (like warehouses or plants) to minimize total costs while meeting demand and capacity constraints.
Core Features & Use Cases
- Problem Classification: Understand and solve Uncapacitated (UFLP), Capacitated (CFLP), p-Median, and p-Center problems.
- Mathematical Modeling: Provides formulations for various FLP types.
- Solution Methods: Implements exact methods (MIP with PuLP), greedy heuristics, local search, and metaheuristics (Simulated Annealing, Genetic Algorithm).
- Use Case: A retail company needs to decide where to open new distribution centers to serve its stores efficiently, considering opening costs, transportation costs, and store demands.
Quick Start
Use the facility-location-problem skill to solve an uncapacitated facility location problem with the provided cost data.
Dependency Matrix
Required Modules
numpypulp
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: facility-location-problem Download link: https://github.com/kishorkukreja/awesome-supply-chain/archive/main.zip#facility-location-problem Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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