Skip to main content
Ctrl+K
    AMPL Resources
  • AMPL.com
  • AMPL Support Forum
  • AMPL Download Portal
  • AMPL Development Resources
    • AMPL + Python 🐍
  • Hands-On Optimization in Python
  • AMPL Model Colaboratory
  • AMPL on Streamlit Cloud
  • amplpy: Python API
    • Open Source Projects
  • rAMPL: R API
  • AMPL Plugins
  • AMPL GSL
  • amplpyfinance
  • Solver Callbacks
  • MP: Solver Interface Framework
    • Licenses & Pricing
  • AMPL & Solvers pricing
  • Free AMPL For Teaching
  • Free AMPL Community Edition
    • Social Media
  • LinkedIn
  • Twitter / X
AMPL Colaboratory - Home AMPL Colaboratory - Home Colaboratory
  • Getting Started
  • Modules
  • Highlights
  • Lectures
  • Authors
  • Tags
  • Notebooks
  • GitHub
  • AMPL Support Forum
  • AMPL Portal
  • AMPL Homepage
  • AMPL Resources
  • Getting Started
  • Modules
  • Highlights
  • Lectures
  • Authors
  • Tags
  • Notebooks
  • GitHub
  • AMPL Support Forum
  • AMPL Portal
  • AMPL Homepage
  • AMPL Resources
Ctrl+K

Section Navigation

  • advertisement (2 notebooks)
  • aircrew-scheduling (1 notebook)
  • ampl (21 notebooks)
  • ampl-book (10 notebooks)
  • ampl-lecture (7 notebooks)
  • ampl-only (21 notebooks)
  • amplpy (50 notebooks)
  • amplpyfinance (1 notebook)
  • ampls (1 notebook)
  • amplxl (1 notebook)
  • arithmetic (1 notebook)
  • assignment (1 notebook)
  • batch-processes (1 notebook)
  • batch-processing (1 notebook)
  • benders (4 notebooks)
  • bin-packing (2 notebooks)
  • bpp (1 notebook)
  • branch-price-and-cut (2 notebooks)
  • callbacks (1 notebook)
  • cbc (7 notebooks)
  • chatgpt (1 notebook)
  • christmas (2 notebooks)
  • classifier (1 notebook)
  • complementarity-problem (1 notebook)
  • complexity (1 notebook)
  • concrete-production (1 notebook)
  • conic (3 notebooks)
  • constraint-programming (5 notebooks)
  • construction-management (1 notebook)
  • convexity (1 notebook)
  • conveyor-based-manufacturing (1 notebook)
  • cpmp (1 notebook)
  • cutting-stock (2 notebooks)
  • dantzig-wolfe-decomposition (2 notebooks)
  • data-analysis (1 notebook)
  • data-driven-model (1 notebook)
  • data-science (1 notebook)
  • data-structures (1 notebook)
  • debug (1 notebook)
  • decision-making (1 notebook)
  • decomposition (4 notebooks)
  • deterministic-model (2 notebooks)
  • disjunctive-programming (1 notebook)
  • educational (4 notebooks)
  • electric-grid (1 notebook)
  • employee-scheduling (1 notebook)
  • energy (2 notebooks)
  • engineering (2 notebooks)
  • example (7 notebooks)
  • excel (2 notebooks)
  • exponential-cone (1 notebook)
  • facility-location (9 notebooks)
  • finance (4 notebooks)
  • formulation-comparison (1 notebook)
  • gcg (2 notebooks)
  • gdp (1 notebook)
  • gecode (1 notebook)
  • geometry (1 notebook)
  • geothermal-energy (1 notebook)
  • gilmore-gomory (1 notebook)
  • global-optimization (1 notebook)
  • google-sheets (2 notebooks)
  • graphs (4 notebooks)
  • gui (2 notebooks)
  • gurobi (3 notebooks)
  • heuristics (2 notebooks)
  • highlights (11 notebooks)
  • highs (9 notebooks)
  • hydropower (1 notebook)
  • indexing (1 notebook)
  • industry (9 notebooks)
  • infeasibility (1 notebook)
  • introduction (4 notebooks)
  • ipopt (1 notebook)
  • json (1 notebook)
  • lecture (1 notebook)
  • lemonade-stand (2 notebooks)
  • lexicographic-optimization (1 notebook)
  • linear-programming (3 notebooks)
  • log-sum-exp (1 notebook)
  • lp (1 notebook)
  • machine-learning (1 notebook)
  • marketing (3 notebooks)
  • max-flow (1 notebook)
  • medicine (1 notebook)
  • military (1 notebook)
  • milp (1 notebook)
  • mip (26 notebooks)
  • mixed-integer-linear (4 notebooks)
  • modeling-tips (1 notebook)
  • mp (4 notebooks)
  • mp-library (1 notebook)
  • multi-objective (1 notebook)
  • multiple-objectives (1 notebook)
  • multiprocess (1 notebook)
  • network (2 notebooks)
  • networkx (1 notebook)
  • non-continuous-objective (1 notebook)
  • non-linear (1 notebook)
  • nonlinear (2 notebooks)
  • nonlinear-programming (1 notebook)
  • oil-production (3 notebooks)
  • optimal-power-flow (5 notebooks)
  • optimization (1 notebook)
  • organ-exchange (1 notebook)
  • pandas (1 notebook)
  • parallel-computing (1 notebook)
  • parallel-solves (1 notebook)
  • piecewise-linear (2 notebooks)
  • planning (1 notebook)
  • power-generation (3 notebooks)
  • powerbi (1 notebook)
  • preferential-bidding-system (1 notebook)
  • price-optimization (1 notebook)
  • pricing (1 notebook)
  • production-optimization (3 notebooks)
  • profitability (4 notebooks)
  • project-management (1 notebook)
  • puzzles (1 notebook)
  • python (6 notebooks)
  • quadratic (1 notebook)
  • quadratic-cone (2 notebooks)
  • quick-start (2 notebooks)
  • refinery (3 notebooks)
  • regression (1 notebook)
  • regularization (1 notebook)
  • reinforced-formulations (1 notebook)
  • residential-developer (1 notebook)
  • risk-management (1 notebook)
  • risk-measures (1 notebook)
  • sample-average-approximation (1 notebook)
  • scheduling (8 notebooks)
  • second-order-cone (2 notebooks)
  • seniority-constraints (1 notebook)
  • seniority-ranking (1 notebook)
  • sequences (1 notebook)
  • sets (1 notebook)
  • shortest-path (1 notebook)
  • sigmoid (1 notebook)
  • simple (1 notebook)
  • softplus (1 notebook)
  • solution-check (1 notebook)
  • spreadsheet (2 notebooks)
  • state-task-networks (1 notebook)
  • stochastic (5 notebooks)
  • stochastic-optimization (1 notebook)
  • stochastic-programming (1 notebook)
  • strict-comparison (1 notebook)
  • supply_chain (2 notebooks)
  • template (1 notebook)
  • trainee-scheduling (1 notebook)
  • transportation (3 notebooks)
  • tsp (1 notebook)
  • unconstrained (1 notebook)
  • unit-commitment (1 notebook)
  • vector-packing (1 notebook)
  • xlsx (1 notebook)
AMPL Python Ecosystem AMPL Python Ecosystem AMPL Model Colaboratory
Hands-On Mathematical Optimization with AMPL in Python

Follow us on Twitter and LinkedIn!

  • Tags
  • convexity

convexity#

Introduction to Mathematical Optimization#

Notebooks > Introduction to Mathematical Optimization
intro_to_optimization.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Basic introduction to optimization and AMPL via unconstrained optimization
Tags: ampl-lecture, amplpy, ampl, introduction, optimization, convexity, unconstrained
Author: Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

previous

construction-management

next

conveyor-based-manufacturing
On this page
  • Introduction to Mathematical Optimization

© Copyright 2022-2024, AMPL Optimization Inc.