Description
Optimization with Python: Solve Operations Research Problems is a training course on optimizing and solving operational research problems with the Python programming language, published by Yodemi Academy. During the course you will use various tools such as CPLEX, Gurobi, Pyomo Optimal Modeling Language, Linear and Nonlinear Programming, Evolution Algorithm and… to solve complex optimization problems. Long-term operational planning for different companies has become very difficult and complex due to the rapid change of available data and the need for fast and periodic decisions, and has faced modern challenges for engineers. In this regard, optimization algorithms are one of our best chances to find optimal solutions to changing problems.During the course of this training, you will work with various libraries and frameworks such as CPLEX, Gurobi, GLPK, CBC, IPOPT, Couenne, SCIP, Pyomo, Or-Tools, PuLP and Pymoo and you will learn very valuable points. Implementing linearization techniques when working with binary variables is another very important educational topic of this course. The instructor of this course has focused more on purely mathematical approaches, but at the same time has also moved on to artificial intelligence, the development of genetic algorithms, and particle swarm optimization methods. This course is designed for beginners and inexperienced in optimization, and in this regard, the first two sections are dedicated to the basic principles of Python programming and mathematical modeling.
What you will learn in the Optimization with Python: Solve Operations Research Problems course:
- Familiarity with different types of optimization such as analytical and meta-heuristic methods
- Linear Programming (LP)
- Integer Linear Programming (MILP)
- Nonlinear Programming (NLP)
- Integer Nonlinear Programming (MINLP)
- Genetic Algorithm (GA)
- Multi-objective optimization with NSGA-II
- Particle swarm optimization (PSO) method
- Constraint Programming (CP)
- Dual Cone Programming (SCOP)
- Optimization of garden fence installation project (covering the most space with the least fence)
- Solve routing problem with optimization techniques
- Maximum revenue increase in car rental store
- Electricity optimization in electrical systems
- Introduction to mathematical modeling
- Understand the basics of the Python programming language
- CPLEX
- Gurobi
- GLPK
- CBC
- IPOPT
- Couenne
- SCIP
- Work with Pyomo, Or-Tools, PuLP and Pymoo frameworks
Course specifications
Publisher: YodemiInstructor: Rafael Silva Pinto
Language: English
Education Level: Basic to Advanced
Number of Courses: 90
Training Duration: 13 hours and 21 minutes
Course topics
Prerequisites for Optimization with Python: Solve Operations Research Problems
Some knowledge in programming logicWhy and where to use optimization
It is NOT necessary to know Python
Course pictures
Introduction to Optimization with Python: Solve Operations Research Problems
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Installation guide
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Download Section 3 - 82 MB