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Operational planning and long term planning for companies are more complex in recent years. Information changes fast, and the decision making is a hard task. Therefore, optimization algorithms (operations research) are used to find optimal solutions for these problems. Professionals in this field are one of the most valued in the market.

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Operational planning and long term planning for companies are more complex in recent years. Information changes fast, and the decision making is a hard task. Therefore, optimization algorithms (operations research) are used to find optimal solutions for these problems. Professionals in this field are one of the most valued in the market.

In this course you will learn what is necessary to solve problems applying Mathematical Optimization and Metaheuristics:

  • Linear Programming (LP)

  • Mixed-Integer Linear Programming (MILP)

  • NonLinear Programming (NLP)

  • Mixed-Integer Linear Programming (MINLP)

  • Genetic Algorithm (GA)

  • Multi-Objective Optimization Problems with NSGA-II (an introduction)

  • Particle Swarm (PSO)

  • Constraint Programming (CP)

  • Second-Order Cone Programming (SCOP)

  • NonConvex Quadratic Programming (QP)

The following solvers and frameworks will be explored:

  • Solvers: CPLEX – Gurobi – GLPK – CBC – IPOPT – Couenne – SCIP

  • Frameworks: Pyomo – Or-Tools – PuLP – Pymoo

  • Same Packages and tools: Geneticalgorithm – Pyswarm – Numpy – Pandas – MatplotLib – Spyder – Jupyter Notebook

Moreover, you will learn how to apply some linearization techniques when using binary variables.

In addition to the classes and exercises, the following problems will be solved step by step:

  • Optimization on how to install a fence in a garden

  • Route optimization problem

  • Maximize the revenue in a rental car store

  • Optimal Power Flow: Electrical Systems

  • Many other examples, some simple, some complexes, including summations and many constraints.

The classes use examples that are created step by step, so we will create the algorithms together.

Besides this course is more focused in mathematical approaches, you will also learn how to solve problems using artificial intelligence (AI), genetic algorithm, and particle swarm.

Don't worry if you do not know Python or how to code, I will teach you everything you need to start with optimization, from the installation of Python and its basics, to complex optimization problems. Also, I have created a nice introduction on mathematical modeling, so you can start solving your problems.

I hope this course can help you in your career. Yet, you will receive a certification from Udemy.

Operations Research | Operational Research | Mathematical Optimization

See you in the classes.

Enroll now

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches mathematical optimization, which is standard in operations research, data science, and artificial intelligence
Develops real-world problem-solving skills using optimization algorithms
Builds a foundation for advanced optimization techniques, machine learning, and data mining
Taught by instructors with extensive experience in optimization and operations research
Uses Python and industry-standard solvers, making it highly relevant to the job market
Requires some familiarity with Python and optimization concepts

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Career center

Learners who complete Optimization with Python: Solve Operations Research Problems will develop knowledge and skills that may be useful to these careers:
Operations Research Analyst
Operations Research Analysts use advanced analytical techniques to solve complex problems in various industries. This course provides a solid foundation in mathematical optimization and metaheuristics, equipping you with the skills to develop and implement solutions for operational planning and long-term decision-making. By mastering these techniques, you'll be well-versed in addressing real-world challenges faced by Operations Research Analysts.
Data Scientist
Data Scientists leverage data to extract insights and drive decision-making. This course enhances your problem-solving abilities through mathematical optimization, enabling you to effectively analyze and interpret complex datasets. The focus on metaheuristics provides you with advanced techniques to handle large-scale and non-linear optimization problems, making you a valuable asset in the field of Data Science.
Management Consultant
Management Consultants provide strategic advice to businesses, helping them improve their operations and achieve their goals. This course empowers you with a comprehensive understanding of optimization techniques, enabling you to analyze business scenarios, identify areas for improvement, and develop data-driven recommendations. The focus on mathematical modeling and linear programming will equip you with the tools to tackle complex decision-making challenges faced by Management Consultants.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to assess financial risks and make investment decisions. This course provides a strong foundation in optimization techniques, including linear programming, non-linear programming, and metaheuristics. By mastering these concepts, you'll gain the skills to develop and implement sophisticated models for risk management and portfolio optimization, making you a sought-after professional in the financial industry.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course provides a comprehensive understanding of optimization algorithms and their implementation in software. By learning to apply mathematical modeling and metaheuristic techniques, you'll be equipped to develop efficient and scalable software solutions for a wide range of industries, including operations research, logistics, and supply chain management.
Supply Chain Manager
Supply Chain Managers optimize the flow of goods and services from suppliers to consumers. This course provides a solid understanding of mathematical optimization and metaheuristics, enabling you to analyze and improve supply chain networks. The focus on linear programming and mixed-integer linear programming will equip you with the tools to design and manage efficient supply chains, reducing costs and improving customer satisfaction.
Business Analyst
Business Analysts bridge the gap between business stakeholders and IT teams, translating business requirements into technical specifications. This course provides a foundation in mathematical modeling and optimization techniques, enabling you to analyze business processes, identify areas for improvement, and develop data-driven solutions. The focus on constraint programming and second-order cone programming will equip you with the skills to handle complex business constraints and optimize decision-making.
Financial Analyst
Financial Analysts evaluate financial data and make recommendations for investments. This course provides a strong foundation in optimization techniques, including linear programming and non-linear programming. By mastering these concepts, you'll gain the skills to develop and implement financial models for risk assessment, portfolio optimization, and investment analysis, making you a valuable asset in the financial industry.
Risk Manager
Risk Managers identify, assess, and mitigate risks to an organization's financial health and reputation. This course provides a comprehensive understanding of optimization techniques, including linear programming and mixed-integer linear programming. By mastering these concepts, you'll gain the skills to develop and implement risk management models, enabling you to make informed decisions and protect your organization from potential threats.
Actuary
Actuaries use mathematical and statistical techniques to assess and manage financial risks. This course provides a strong foundation in optimization techniques, including linear programming and non-linear programming. By mastering these concepts, you'll gain the skills to develop and implement actuarial models for insurance pricing, risk assessment, and financial planning, making you a valuable asset in the insurance industry.
Statistician
Statisticians collect, analyze, interpret, and present data. This course provides a solid understanding of optimization techniques, including linear programming and non-linear programming. By mastering these concepts, you'll gain the skills to develop and implement statistical models for data analysis, hypothesis testing, and forecasting, making you a valuable asset in various fields such as research, healthcare, and marketing.
Economist
Economists analyze economic trends and data to develop policies and make predictions. This course provides a foundation in mathematical modeling and optimization techniques, enabling you to analyze economic data, forecast economic outcomes, and develop data-driven policy recommendations. The focus on linear programming and mixed-integer linear programming will equip you with the tools to handle complex economic models and optimize decision-making.
Operations Manager
Operations Managers oversee the day-to-day operations of an organization. This course provides a comprehensive understanding of optimization techniques, including linear programming and mixed-integer linear programming. By mastering these concepts, you'll gain the skills to analyze and improve operational processes, reduce costs, and increase efficiency, making you a valuable asset in any industry.
Project Manager
Project Managers plan, execute, and close projects. This course provides a solid understanding of optimization techniques, including linear programming and non-linear programming. By mastering these concepts, you'll gain the skills to develop and implement project plans, allocate resources, and manage risks, making you an effective Project Manager in any industry.
Consultant
Consultants provide advice and expertise to organizations on a variety of topics. This course provides a foundation in mathematical modeling and optimization techniques, enabling you to analyze business scenarios, identify areas for improvement, and develop data-driven recommendations. By mastering these techniques, you'll become a valuable asset to clients in various industries, helping them solve complex problems and achieve their goals.

Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Optimization with Python: Solve Operations Research Problems.
Provides a comprehensive introduction to operations research, a field that uses mathematical and analytical techniques to solve problems in business, industry, and government.
Provides a thorough treatment of convex optimization, a powerful tool for solving a wide range of problems in fields such as finance, engineering, and operations research.
Provides a comprehensive introduction to linear programming, with a focus on MATLAB-based tools and techniques.
Provides a comprehensive treatment of nonlinear programming, a more general form of optimization that allows for nonlinear constraints and objective functions.
Provides a comprehensive introduction to genetic algorithms, a powerful metaheuristic for solving complex optimization problems.
Provides a comprehensive introduction to particle swarm optimization, a powerful metaheuristic for solving complex optimization problems.
Provides a comprehensive introduction to constraint programming, a powerful tool for solving combinatorial optimization problems.
Provides a comprehensive introduction to practical optimization, with a focus on real-world applications.
Provides a comprehensive introduction to multi-objective optimization, a powerful tool for solving problems with multiple objectives.
Provides a comprehensive introduction to nonconvex quadratic programming, a more general form of optimization that allows for nonconvex constraints and objective functions.

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