Learning journal unit 6

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University of Colorado, Denver *

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3304

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Computer Science

Date

Jan 9, 2024

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docx

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Uploaded by daveakston

Describe what you did. This does not mean that you copy and paste from what you have posted or the assignments you have prepared. You need to describe what you did and how you did it. I always start new unit with going through learning guide and see what we have to deal with for the week. This helps me to plan my time, like how many days I need for reading or any assignments. I usually do everything by order like reading first, then discussion, then written assignment, then learning guide and any quizzes we have for a unit. Since this week we did not have written assignment, it saved me time to study for my graded quiz. For the discussion assignment, we needed to discuss real-world implementations of the simplex method. We were given details on the percentages of polyester and cotton used in manufacturing, the availability of the fabrics, and the factory’s quality control measures for the final products. We were provided with the profit margins for both items per unit sold and instructed to optimize those margins within the above parameters. The equalities were graphed to discover the maximum point or placed in a two-dimensional matrix and reduced using Tableau. Our response has been submitted and is available in the discussion forum. After I posted my discussion assignment, I went through my classmates’ posts and read them and rated them. They all did great work, and I took some notes for their posts for myself. After being done with discussion assignment I took a self-quiz, then graded quiz, and then I rated my classmates’ assignments from the previous unit. Describe your reactions to what you did. I have learned that linear programming has nothing to do with programming (coding) as the term suggests. However, it has to do with planning and the use of mathematical techniques to determine an optimum answer for an optimization problem. The technique is said to be widely used in optimization tasks where the optimization tasks and constraint criteria are linear functions. Describe any feedback you received or any specific interactions you had. Discuss how they were helpful. I found the discussion forum responses to be highly beneficial, enhancing my understanding of the course materials. The examples shared by others proved particularly helpful. Constructive feedback from my peers has been a valuable source of both personal growth and motivation. Engaging in the forum not only kept my classmates informed about my progress but also improved my ability to engage in more fruitful discussions about classwork. Describe your feelings and attitudes. This week’s learning was not complicated to me, well, I had to work a little bit hard to get my discussion assignment completed. But that did not make me to give up on an assignment, I just needed to get a break and then go back with clear mind. Describe what you learned. We studied linear programming and the application of the simplex algorithm to implement solutions, forming the foundation for our discussion assignment as well. Linear programming is mathematical modeling technique in which a linear function is maximized or minimized when

subjected to various constraints. It comprises linear functions constrained by linear equations or inequalities. A common objective in linear programming is to optimize the utilization of available resources. Various methods can be employed to address linear programming problems, including the use of software packages such as Open Solver and R, the simplex method, and graphical techniques (Avcontentteam, 2023). I have learned how to solve linear programs inefficient manner using the simplex algorithm. This algorithm achieves optimization by taking the linear objective function and all the linear inequalities defined in finding the optimal solution using the matrix methodology. Before using the matrix methodology, the simplex algorithm rewrites the problem and the constraints. The problem function is negated, and the inequalities constraints are rewritten by including a sliding variable that changes inequalities equations to equality equations. From there, we create a matrix from these equalities’ equations. Then, iterate through the matrix to reduce the equations, each time we make a loop we will have to identify the pivot column, and the pivot values and reduce all the functions based on the selected column and pivot. Reference list: Avcontentteam. (2023, May 11). What is linear programming? Definition, methods and problems for data scientists . Analytics Vidhya. https://www.analyticsvidhya.com/blog/2017/02/lintroductory-guide-on-linear- programming-explained-in-simple-english/

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