Description
Optimization with Python: Solve Operations Research Problems is a training course on optimization problems and solving operations research problems with the Python programming language, which was published by Yudemy Academy. During this training course, you will use various tools such as CPLEX, Gurobi, Pyomo optimal modeling language, linear and non-linear programming, evolutionary algorithm, etc. to solve complex optimization problems. Operational and long-term planning for various companies has become very difficult and complicated due to the rapid change of available data and the necessity of quick and periodic decisions, and has made engineers face modern challenges. In this regard, optimization algorithms are one of our best chances to find optimal solutions for changing problems.
During this training course, 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 valuable tips. Implementation of 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 pure mathematical approaches, but at the same time, he has also made a transition to artificial intelligence, development of genetic algorithms, particle swarm optimization method. This course is designed for beginners and inexperienced people in optimization, and in this regard, the first two parts are dedicated to the introductory principles of Python programming and mathematical modeling.
What you will learn in the course Optimization with Python: Solve Operations Research Problems:
- Familiarity with different types of optimization such as analytical and meta-heuristic methods
- linear programming (LP)
- mixed integer linear programming (MILP)
- non-linear programming (NLP)
- Mixed 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)
- Optimizing the fence installation project around the garden (covering the most space with the least fence)
- Solving the routing problem with optimization techniques
- Maximum increase of income in car rental shop
- Optimization of electric current in electrical systems
- Familiarity with mathematical modeling
- Understanding the basics of the Python programming language
- CPLEX
- Gurobi
- GLPK
- CBC
- IPOPT
- Couenne
- SCIP
- Working with Pyomo, Or-Tools, PuLP and Pymoo frameworks
Course details
Publisher: Yodmi
teacher: Rafael Silva Pinto
English language
Training level: introductory to advanced
Number of courses: 90
Training duration: 13 hours and 21 minutes
Course headings
Prerequisites for the course Optimization with Python: Solve Operations Research Problems
Some knowledge in programming logic
Why and where to use optimization
It is NOT necessary to know Python
Course images
Introduction video of the course Optimization with Python: Solve Operations Research Problems
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
download link
Password file(s): www.downloadly.ir
Size
2.08 GB
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