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Emmanuel Jesuyon Dansu
Приєднався 6 тра 2012
Explore the elegant intersections of math, life's complexities, and timeless wisdom in one captivating channel.
14. Setting Up the Simplex Tableau
In this video, we delve into the fundamentals of setting up a simplex tableau for solving linear programming problems.
We cover everything from identifying the objective function to incorporating slack and artificial variables.
Through clear examples, you'll learn how to transform constraints into equations and organize your tableau for effective computation.
This essential skill will enhance your problem-solving toolkit in optimization and operations research.
Don’t forget to like, subscribe, and hit the notification bell for more math tutorials!
#SimplexMethod #LinearProgramming #Optimization #MathTutorial #OperationsResearch #SlackVariables #ArtificialVariables #TableauSetup #MathEducation #ProblemSolving
We cover everything from identifying the objective function to incorporating slack and artificial variables.
Through clear examples, you'll learn how to transform constraints into equations and organize your tableau for effective computation.
This essential skill will enhance your problem-solving toolkit in optimization and operations research.
Don’t forget to like, subscribe, and hit the notification bell for more math tutorials!
#SimplexMethod #LinearProgramming #Optimization #MathTutorial #OperationsResearch #SlackVariables #ArtificialVariables #TableauSetup #MathEducation #ProblemSolving
Переглядів: 8
Відео
13. Linear Programming Forms
Переглядів 502 години тому
In this video, we dive into the different forms of linear programming: canonical, standard, and matrix forms. These forms are essential for understanding and solving linear programming problems efficiently, especially when applying optimization techniques like the Simplex Method. We'll break down each form's structure, explain how they differ, and show why these distinctions matter for solving ...
12. Introduction to Simplex Method
Переглядів 152 години тому
In this video, we explore the Simplex Method, a powerful algorithm used to solve linear programming (LP) problems efficiently. We'll provide an overview of its key concepts, including its importance in tackling higher-dimensional LP challenges and different linear programming forms such as canonical, standard, and matrix. Whether you're a student or a professional, understanding the Simplex Met...
11. Python Code for a Cost Minimisation Problem
Переглядів 164 години тому
In this video, we explore a fascinating real-world application of linear programming as we help a hospital determine the optimal order quantities for two medications, Med A and Med B. By analyzing constraints related to budget, storage capacity, and patient demand, we aim to minimize the hospital's costs while ensuring adequate medication supply. Watch as we break down the problem, formulate th...
10. Graphical Solution to a Cost Minimisation Problem
Переглядів 114 години тому
In this video, we dive into a practical application of linear programming to help a hospital optimize its medication orders for Med A and Med B. Faced with constraints on budget, storage, and patient demand, we demonstrate how to minimize costs while ensuring that all requirements are met. Join us as we walk through the problem-solving process step by step, from formulating the objective functi...
9. Special Cases in Graphical Solutions: Unbounded Solutions
Переглядів 114 години тому
In this video, we explore the concept of unbounded solutions in linear programming through a practical example. We analyze the problem of maximizing the objective function z=2x y under specific constraints and illustrate how the feasible region allows for infinite growth in the objective function, leading to unbounded solutions. Join us as we break down the steps of graphical representation, in...
8. Special Cases in Graphical Solutions: Infeasible Solutions
Переглядів 124 години тому
In this video, we delve into the concept of infeasibility in linear programming using a specific example: maximizing the objective function z=x y under conflicting constraints. We explore how the constraints x y≥5 and x y≤3 create incompatible regions, leading to an infeasible solution space. Through graphical representation and analysis, viewers will gain a clear understanding of why some line...
7. Special Cases in Graphical Solutions: Multiple Optimal Solutions
Переглядів 134 години тому
In this video, we explore the concept of multiple optimal solutions in linear programming through a detailed example. We maximize the objective function z=8x 6y under given constraints, identifying the feasible region and evaluating key corner points to uncover how multiple solutions can yield the same optimal value. Join us as we break down the steps to solve this linear programming problem, m...
6. Python Code for a Profit Maximisation Problem
Переглядів 164 години тому
In this video, we dive into the solution of a profit maximization problem using Python! We'll guide you step-by-step through the implementation of linear programming with the scipy.optimize.linprog function to determine the optimal quantities of Wrist Watches and Pocket Watches to manufacture. Watch as we break down the code, explaining the formulation of the objective function and constraints,...
5. Graphical Solution to a Profit Maximisation Problem
Переглядів 154 години тому
In this video, we explore the graphical solution to a profit maximization problem involving the production of Wrist Watches and Pocket Watches. We break down the process of setting up the linear programming model, defining the objective function, and establishing constraints based on machine availability. Through step-by-step visualizations, we demonstrate how to find the feasible region and id...
4. Graphical Method Overview for Solving Linear Programming Problems
Переглядів 469 годин тому
In this video, we explore the graphical method for solving two-variable linear programming problems. You'll learn the essential steps to graph constraints, identify the feasible region, and find the optimal solution through visual representation. Whether you're a student or a professional looking to enhance your optimization skills, this tutorial provides clear insights and practical examples t...
3. Setting up a Linear Programming Problem
Переглядів 279 годин тому
In this video, we explore how to set up Linear Programming (LP) problems from real-world scenarios, focusing on practical examples in business and manufacturing. Learn the step-by-step process of defining decision variables, formulating objective functions, and establishing constraints, as we work through problems like maximizing advertising reach and minimizing production costs. Whether you're...
Opportunities w/EJD || Questions & Answers on Scholarships || Dr. Emmanuel J. Dansu || 02.11.2024
Переглядів 309 годин тому
In this episode of Opportunities w/EJD, Dr. Emmanuel J. Dansu dives into an interactive Q&A session focused on scholarships, sharing valuable insights, tips, and resources for students aiming to secure educational funding. Tune in as Dr. Dansu answers real questions from viewers, covering everything from application strategies to maximizing scholarship opportunities. Whether you're a first-time...
2. Key Terminology in Linear Programming
Переглядів 2812 годин тому
In this video, we break down the essential terminology in linear programming, including objective function, constraints, feasible region, decision variables, and optimal solution. Each term is defined clearly with practical examples to help you understand how linear programming models are structured and solved. Whether you’re maximizing profits, minimizing costs, or optimizing resources, master...
1. What is Linear Programming?
Переглядів 4214 годин тому
In this video, we dive into the basics of Linear Programming (LP), a fundamental tool in optimization used across industries to solve real-world problems by maximizing or minimizing outcomes like profit or cost. We cover its history, developed during WWII for efficient resource allocation, and explore its structure, which includes an objective function, variables, and constraints. You'll learn ...
35. Python Code for MANOVA (Multivariate Analysis of Variance)
Переглядів 2116 годин тому
35. Python Code for MANOVA (Multivariate Analysis of Variance)
34. Python Code for Mixed-Design or Split-Plot ANOVA (Analysis of Variance)
Переглядів 2316 годин тому
34. Python Code for Mixed-Design or Split-Plot ANOVA (Analysis of Variance)
33. Python Code for Repeated Measures ANOVA (Analysis of Variance)
Переглядів 2116 годин тому
33. Python Code for Repeated Measures ANOVA (Analysis of Variance)
32. Python Code for Two-Way ANOVA (Analysis of Variance)
Переглядів 2319 годин тому
32. Python Code for Two-Way ANOVA (Analysis of Variance)
31. Two-Way ANOVA (Analysis of Variance)
Переглядів 3319 годин тому
31. Two-Way ANOVA (Analysis of Variance)
30. Python Code for One-Way ANOVA (Analysis of Variance)
Переглядів 20День тому
30. Python Code for One-Way ANOVA (Analysis of Variance)
29. One-Way ANOVA (Analysis of Variance)
Переглядів 49День тому
29. One-Way ANOVA (Analysis of Variance)
FEM 5: Rank Correlation and Paired t-Test
Переглядів 18День тому
FEM 5: Rank Correlation and Paired t-Test
FEM 4: French Study Duration and Test Grades
Переглядів 2814 днів тому
FEM 4: French Study Duration and Test Grades
FEM 3: Student Marks Analysis and Grouped Frequency
Переглядів 2014 днів тому
FEM 3: Student Marks Analysis and Grouped Frequency
FEM 2: Scales of Measurement and Coded Formula Approach for Mean & Deviation
Переглядів 3014 днів тому
FEM 2: Scales of Measurement and Coded Formula Approach for Mean & Deviation
FEM 1: Statistics Types & Statistical Tests
Переглядів 3114 днів тому
FEM 1: Statistics Types & Statistical Tests
Service As A Tangible Experience || Clementina Busayo @clementinabusayo || Emmanuel Dansu || 191024
Переглядів 3814 днів тому
Service As A Tangible Experience || Clementina Busayo @clementinabusayo || Emmanuel Dansu || 191024
ES 6: Parabola Least-Squares Fitting and More
Переглядів 3314 днів тому
ES 6: Parabola Least-Squares Fitting and More
ES 5: Combined Statistics and Error Types
Переглядів 1914 днів тому
ES 5: Combined Statistics and Error Types
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Very useful video. Thank you Emmanuel!
@@AndreyTodz It is my pleasure.
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Great video, your explanations are concise and easy to follow. Just found this series, I'm definitely following it 👍
Aw! That's so good to know. Please feel very free to subscribe, hit the notification bell, like, and share.
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Thank you for the gift of your time and for your insights on the Service-As-A-Tangible Experience conversation
@@clementinabusayo Thank you so much, CEO! It was such a nice conversation.
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Great Stuff!
Thank you so much!
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Insightful 💯
Thank you so much, Sis.
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Nice explanation.
Well explained!
Thank you so much!
Great job!
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All singles should listen to this webinar. Thank you for this wonderful webinar sir
Always our pleasure.