Here you might find some examples and tutorials on numerical optimization.
A comprehensive Python course featuring several of these examples can be found HERE.
Check my Medium profile for some interesting articles about (most of) these examples.
- Implementation from scratch of usual gradient-based line search algorithms in Python.
- Solution of a constrained problem using the scipy.optimize minimize function.
- Optimization of a chemical reactor problem.
- Applications of nonlinear optimization to classification problems.
- Variants of the knapsack problem: simple, multi-dimensional and multiple knapsacks.
- Dynamic lot-size model
- Job-shop scheduling (external repository)
- Branch & Bound graphical example and pure Python implementation from scratch
- Cutting stock problem
- Capacitated vehicle routing problem (CVRP)
- Graph Coloring Problem
- Maximum Independent Set
- Piecewise linear
- Implementation Differential Evolution using scipy.optimize.
- Solutions of convex, nondifferentiable, and nonconvex problems using DE and classic algorithms.
- Implementation of Linear Regression from scratch in Python.
- Examples of Linear Regression applications, residual analysis, and feature selection.
- Capacitated vehicle routing problem (CVRP): Heuristics
- Graph Coloring Problem: DSatur Heuristics and ILP
- Maximum Independent Set: Greedy and Random heuristics and ILP
- Knapsack Problem: Greedy heuristics
- Portfolio Efficient Frontier: Modern Portfolio Theory using a multi-objective approach with pymoo and pymoode.