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pyomo

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Master Pyomo optimization in Python

Software Engineering#python#optimization#modeling#pyomo#solver#dae#gdp
Authorsverzijl
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Pyomo is a Python-based optimization modeling library that enables building, solving, and analyzing mathematical programs, removing the friction of switching between modeling languages and solvers.

Core Features & Use Cases

  • Modeling versatility: LP, MILP, NLP, MINLP, and generalized disjunctive programming (GDP) models.
  • Dynamic optimization: Differential equations and DAEs with pyomo.dae, including discretization and simulation.
  • Solver integration: Interfaces to open-source and commercial solvers (GLPK, CBC, IPOPT, Gurobi, CPLEX) and solver workflows for parametric studies and scenario analysis.
  • Reference-rich guidance: Access comprehensive API, tutorials, and usage patterns in the included references directory for self-paced learning and advanced usage.

Quick Start

Install Pyomo and a solver, then create a minimal Pyomo model in Python, solve it with a solver, and print the results. Example steps:

  • Install: pip install pyomo
  • Create a simple ConcreteModel with two variables, an objective, and a constraint.
  • Solve with e.g., SolverFactory('glpk') and display variable values.

Dependency Matrix

Required Modules

None required

Components

references

💻 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: pyomo
Download link: https://github.com/sverzijl/planning_latest/archive/main.zip#pyomo

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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