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Moses Gummadi
For a given demand profile for 8 products over a 9 week period, we determine the optimal production plan for minimal inventory. "Mixed Integer Linear Programming" method is applied using R lpSolve library.
Register for this course and see more details by visiting:
OpenCourser.com/course/d4z50f/multi
What's inside
Syllabus
Project Overview
Welcome to "Multi Product Optimal Production Planning Using R lpSolveAPI". This is a project-based course which should take under 2 hours to finish. Before diving into the project, please take a look at the course objectives and structure. By the end of this project, you will gain introductiory knowledge of Multi Product Production Planning, Mixed Integer Linear Programming (MILP), be able to use R Studio and lpSolveAPI library, formulate pptmisation problem & determine the objective function, apply constraints, run optimiser, obtain & analyse the solution.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces Multi Product Production Planning, Mixed Integer Linear Programming (MILP), which are foundational concepts in various domains
Provides practical experience in using R Studio and the lpSolveAPI library, equipping learners with industry-relevant tools
Emphasizes formulating optimization problems, determining objective functions, and applying constraints, enhancing problem-solving skills
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Save Multi Product Optimal Production Planing Using R lpSolveAPI to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Multi Product Optimal Production Planing Using R lpSolveAPI with these
activities:
Review Linear Programming and Network Flows (3rd Edition)
Show steps
Review a foundational text on linear programming to strengthen understanding of the concepts and techniques covered in the course.
View
Linear Programming and Network Flows
on Amazon
Show steps
-
Read selected chapters
-
Solve practice problems
Learn R lpSolveAPI library
Show steps
Follow tutorials to learn how to use the R lpSolveAPI library for solving linear programming problems.
Browse courses on
R
Show steps
-
Install the R lpSolveAPI library
-
Load the R lpSolveAPI library
-
Create a linear programming model using the R lpSolveAPI library
-
Solve the linear programming model using the R lpSolveAPI library
-
Interpret the solution to the linear programming model
Practice formulating MIP problems
Show steps
Practice formulating Mixed Integer Programming (MIP) problems to improve understanding of the modeling process.
Browse courses on
Mixed Integer Programming
Show steps
-
Identify decision variables
-
Define objective function
-
Formulate constraints
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve linear programming problems
Show steps
Practice solving linear programming problems to improve understanding of the concepts and techniques covered in the course.
Browse courses on
Linear Programming
Show steps
-
Identify linear programming problems
-
Formulate linear programming models
-
Apply the Simplex method
Participate in discussion forums
Show steps
Engage in discussions with peers to clarify concepts, share insights, and get different perspectives on the course material.
Show steps
-
Join the discussion forums
-
Post questions
-
Respond to posts
Answer questions in discussion forums
Show steps
Provide support and guidance to peers by answering questions in the discussion forums.
Show steps
-
Join the discussion forums
-
Monitor posts
-
Provide thoughtful and helpful responses
Develop a case study
Show steps
Apply the concepts of multi-product optimal production planning covered in the course to a real-world business scenario.
Browse courses on
Case study
Show steps
-
Identify a business scenario
-
Collect data
-
Formulate a linear programming model
-
Solve the linear programming model
-
Analyze the results
Review Linear Programming and Network Flows (3rd Edition)
Show steps
Review a foundational text on linear programming to strengthen understanding of the concepts and techniques covered in the course.
View
Linear Programming and Network Flows
on Amazon
Show steps
Show steps
Show steps
- Read selected chapters
- Solve practice problems
Learn R lpSolveAPI library
Show steps
Follow tutorials to learn how to use the R lpSolveAPI library for solving linear programming problems.
Browse courses on
R
Show steps
Show steps
Show steps
- Install the R lpSolveAPI library
- Load the R lpSolveAPI library
- Create a linear programming model using the R lpSolveAPI library
- Solve the linear programming model using the R lpSolveAPI library
- Interpret the solution to the linear programming model
Practice formulating MIP problems
Show steps
Practice formulating Mixed Integer Programming (MIP) problems to improve understanding of the modeling process.
Browse courses on
Mixed Integer Programming
Show steps
Show steps
Show steps
- Identify decision variables
- Define objective function
- Formulate constraints
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve linear programming problems
Show steps
Practice solving linear programming problems to improve understanding of the concepts and techniques covered in the course.
Browse courses on
Linear Programming
Show steps
Show steps
Show steps
- Identify linear programming problems
- Formulate linear programming models
- Apply the Simplex method
Participate in discussion forums
Show steps
Engage in discussions with peers to clarify concepts, share insights, and get different perspectives on the course material.
Show steps
Show steps
Show steps
- Join the discussion forums
- Post questions
- Respond to posts
Answer questions in discussion forums
Show steps
Provide support and guidance to peers by answering questions in the discussion forums.
Show steps
Show steps
Show steps
- Join the discussion forums
- Monitor posts
- Provide thoughtful and helpful responses
Develop a case study
Show steps
Apply the concepts of multi-product optimal production planning covered in the course to a real-world business scenario.
Browse courses on
Case study
Show steps
Show steps
Show steps
- Identify a business scenario
- Collect data
- Formulate a linear programming model
- Solve the linear programming model
- Analyze the results
Career center
Learners who complete Multi Product Optimal Production Planing Using R lpSolveAPI will develop knowledge and skills
that may be useful to these careers:
Production Planner
Production Planner
Production planners develop and implement production schedules to ensure that products are manufactured efficiently and meet customer demand. This course provides practical knowledge of production planning techniques, including MILP, which is widely used in the field. You will learn how to optimize production plans considering factors such as demand, capacity, and inventory levels. This course will enhance your ability to make informed decisions and improve production efficiency.
Operations Research Analyst
Operations Research Analyst
Operations research analysts use mathematical and analytical techniques to solve complex problems in various industries, including manufacturing, transportation, and healthcare. This course provides a solid foundation in mixed integer linear programming (MILP), a powerful technique used in operations research to optimize production plans and minimize inventory. By learning how to formulate optimization problems, apply constraints, and analyze solutions, you will gain valuable skills that can directly benefit your work as an operations research analyst.
Supply Chain Manager
Supply Chain Manager
Supply chain managers oversee the flow of goods, services, and information within a supply chain. This course provides insights into production planning, an essential aspect of supply chain management. By understanding how to optimize production plans, you can improve inventory management, reduce lead times, and enhance overall supply chain performance. This course will help you build a foundation in supply chain management and prepare you for this challenging role.
Management Consultant
Management Consultant
Management consultants analyze business operations and provide recommendations to improve efficiency and effectiveness. This course provides a valuable introduction to mathematical modeling and optimization techniques, which are commonly used in consulting projects. By learning how to formulate and solve optimization problems, you can develop analytical skills that are highly sought after by management consulting firms. This course will help you build a strong foundation for a successful career in management consulting.
Data Scientist
Data Scientist
Data scientists use statistical and computational methods to extract insights from data. This course provides a foundation in mathematical modeling, which is essential for data science. By learning how to formulate and solve optimization problems, you will develop analytical skills that are highly valued in the data science field. This course will help you build a foundation for a successful career as a data scientist.
Business Analyst
Business Analyst
Business analysts analyze business processes and identify opportunities for improvement. This course provides a valuable introduction to mathematical modeling and optimization techniques, which are becoming increasingly important in business analysis. By learning how to formulate and solve optimization problems, you can develop analytical skills that are highly sought after by businesses. This course will help you build a foundation for a successful career as a business analyst.
Project Manager
Project Manager
Project managers plan, execute, and close projects. This course provides a valuable introduction to mathematical modeling and optimization techniques, which are becoming increasingly important in project management. By learning how to formulate and solve optimization problems, you can develop analytical skills that are highly sought after by organizations. This course will help you build a foundation for a successful career as a project manager.
Financial Analyst
Financial Analyst
Financial analysts evaluate investments and provide financial advice to clients. This course provides a foundation in mathematical modeling, which is essential for financial analysis. By learning how to formulate and solve optimization problems, you will develop analytical skills that are highly valued in the financial industry. This course will help you build a foundation for a successful career as a financial analyst.
Risk Analyst
Risk Analyst
Risk analysts identify, assess, and manage risks. This course provides a valuable introduction to mathematical modeling and optimization techniques, which are becoming increasingly important in risk analysis. By learning how to formulate and solve optimization problems, you can develop analytical skills that are highly sought after by organizations. This course will help you build a foundation for a successful career as a risk analyst.
Operations Manager
Operations Manager
Operations managers plan, organize, and control the operations of an organization. This course provides a valuable introduction to mathematical modeling and optimization techniques, which are becoming increasingly important in operations management. By learning how to formulate and solve optimization problems, you can develop analytical skills that are highly sought after by organizations. This course will help you build a foundation for a successful career as an operations manager.
Industrial Engineer
Industrial Engineer
Industrial engineers design, improve, and install integrated systems for managing industrial production. This course provides a valuable introduction to mathematical modeling and optimization techniques, which are widely used in industrial engineering. By learning how to formulate and solve optimization problems, you can develop analytical skills that are highly sought after by industrial engineering firms. This course will help you build a foundation for a successful career as an industrial engineer.
Systems Analyst
Systems Analyst
Systems analysts design, develop, and implement computer systems. This course provides a valuable introduction to mathematical modeling and optimization techniques, which are becoming increasingly important in systems analysis. By learning how to formulate and solve optimization problems, you can develop analytical skills that are highly sought after by systems analysis firms. This course will help you build a foundation for a successful career as a systems analyst.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software systems. This course provides a valuable introduction to mathematical modeling and optimization techniques, which are becoming increasingly important in software engineering. By learning how to formulate and solve optimization problems, you can develop analytical skills that are highly sought after by software engineering firms. This course will help you build a foundation for a successful career as a software engineer.
Market Researcher
Market Researcher
Market researchers collect, analyze, and interpret data about markets and consumers. This course provides a valuable introduction to mathematical modeling and optimization techniques, which are becoming increasingly important in market research. By learning how to formulate and solve optimization problems, you can develop analytical skills that are highly sought after by market research firms. This course will help you build a foundation for a successful career as a market researcher.
Data Analyst
Data Analyst
Data analysts collect, analyze, and interpret data to help organizations make better decisions. This course provides a valuable introduction to mathematical modeling and optimization techniques, which are becoming increasingly important in data analysis. By learning how to formulate and solve optimization problems, you can develop analytical skills that are highly sought after by organizations. This course will help you build a foundation for a successful career as a data analyst.
For more career information including salaries, visit:
OpenCourser.com/course/d4z50f/multi
Reading list
We've selected nine 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
Multi Product Optimal Production Planing Using R lpSolveAPI.
Save
Offers a comprehensive treatment of linear programming, providing a solid foundation for understanding and solving linear optimization problems. It covers topics such as simplex method, duality theory, and sensitivity analysis, making it a valuable reference for both beginners and experienced practitioners.
This classic textbook provides a broad overview of operations research, including topics such as linear programming, inventory management, and queuing theory. It offers a solid foundation for understanding the principles and techniques used in production planning and optimization.
This textbook provides a comprehensive overview of production and operations management, covering topics such as forecasting, inventory management, and production planning. It offers a practical approach to understanding and managing production systems.
Save
This foundational book provides a comprehensive treatment of linear optimization, including advanced topics such as nonlinear programming and integer programming. It offers a rigorous and in-depth understanding of the theoretical underpinnings of optimization methods.
Save
This authoritative reference provides a comprehensive overview of integer programming, covering both theoretical foundations and practical applications. It offers advanced insights for researchers and practitioners working with integer optimization problems.
This classic textbook provides a comprehensive overview of production planning and inventory control, covering topics such as forecasting, inventory management, and production scheduling. It offers a practical approach to understanding and managing production systems.
This comprehensive textbook provides a rigorous treatment of linear programming and network flows, covering both theoretical foundations and practical applications. It offers advanced insights for researchers and practitioners working with optimization problems.
This introductory textbook provides a clear and concise overview of mathematical programming, covering topics such as linear programming, nonlinear programming, and integer programming. It offers a solid foundation for understanding the principles and techniques used in optimization problems.
This practical guide provides a hands-on approach to using MATLAB for linear programming. It covers topics such as model formulation, solution techniques, and sensitivity analysis, making it a valuable resource for practitioners who want to apply optimization techniques using MATLAB.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/d4z50f/multi
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Effort
2 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Moses Gummadi
Language
English
Good to know
Introduces Multi Product Production Planning, Mixed Integer Linear Programming (MILP), which are foundational concepts in various domains
Provides practical experience in using R Studio and the lpSolveAPI library, equipping learners with industry-relevant tools
Emphasizes formulating optimization problems, determining objective functions, and applying constraints, enhancing problem-solving skills
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