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Thanks for your contribution..

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Sorry guys, kind of busy this day...

Hope you guys got notice that Dr. already extend the due date until after mid semester break..

Since we finish our work already so i will upload our video here..

Thanks for your contribution..

Really appreciate it and hope we can work together afterwards..

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guys, remember to record your video and insert in here yaa..

later we can create a video from this

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Guys don't forget our due date will be on 11 NOV 2024

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Guys don't forget our due date will be on 11 NOV 2024

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AND OUR INTERNAL DUE WILL BE 9 NOV 2024

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Guys, after you finish your work pls send here yaa, we can discuss

*internal DUE 9 NOV 2024

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In the graphical analysis of a LP model, what occurs when the slope of the objective function is the same as the slope of one of the constraint equations?

When the objective function's slope is the same as a constraint's slope, the objective function line is parallel to that constraint. This situation often results in multiple optimal solutions along a line segment if that constraint forms part of the boundary of the feasible region.

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6) What constitutes the feasible solution area on the graph of a LP model?

The feasible area is the graph region that satisfies all constraints at the same time. It is usually a polygon created by the intersection of constraint lines. Any point inside or on the border of this region is a feasible solution.

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5) In the graphical solution method, explain how a constraint and the objective function are plotted on the graph.

· Constraint: Convert each inequality constraint into an equation by setting it equal. Plot this line, and then shade the area that satisfies the inequality.

· Objective Function: Plot the objective function as a line by assigning it an arbitrary value. Adjust its position parallel to itself to maximize or minimize the function while staying within the feasible region.

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4) What are the benefits of the graphical method for solving LP problems?

-It helps the identification of the feasible area and optimal solution points, providing insight into how constraints interact with the objective function.

-It is useful for introducing LP principles and developing intuition on feasible regions, optimal solutions, and trade-offs.

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My name is Muhammad Arif Nurhakim Bin Mazlan, just call me Hakim. My matric number is 294092 under Management of Technology from STML. I'm from Port Dickson, Negeri Sembilan and currently staying at inasis YAB. Here's my contact 0195860370.

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8) In the graphical analysis of a LP problem, how does the determination of a solution differ between a maximization problem and a minimization problem?

In a maximization problem,the objective function line is shifted outwards to the extreme of the feasible region

In a minimization problem, the objective function line is shifted towards the most minimal value of the feasible region

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Answer for Question 1: Steps For Solving LP 

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Answer for Question 1: Steps For Solving LP 

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What are the limitations of the graphical method for solving LP problems?

Dimension Limitation: Only works with two decision variables (and sometimes three with complex 3D methods), which is impractical for most real-world LP problems with more variables.

Accuracy and Precision: Visual methods may lack precision compared to algebraic or software-based solutions.

Complexity in Constraints: When there are many constraints, interpreting the feasible region can become visually complex.

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Who can help to ask Dr about our work tomorrow after class?

Because I got class after this🥲I’m afraid I cannot…

If can just comment here 🫶🏻🥲

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Hi guys!! I am Aw Seng Kang from Operation Management. My matric no. is 298366 and I'm from Kota Tinggi,Johor. Currently, I'm living at Inasis TM. My phone number is 0182967335.

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https://docs.google.com/document/d/1WGdSghKeC0rCSoKCZHo5gJRITtdtghfWrt3oouMy7j8/edit?usp=sharing

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Guys for the video recording, each people limit for 5 minutes ya

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guys, for the work tag will be red colour yaa

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7) How is the optimal solution point identified on the graph of a LP model?

The best solution often arrived at the extreme point of the feasible region polygonal boundary or the vertices.

To solve the maximization problem, we need to slide the objective function line in the direction that hikes the value of an objective to the last point of the feasible area

To solve the minimization problem we need to slide it in the direction that lowers down the value of an objective to the last point of the feasible region

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hi guyss, now i distribute your work yaa

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hi guyss, now i distribute your work yaa

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these three questions are for SengKang

*if got any problem we can discuss under comment

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hi guyss, now i distribute your work yaa

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hi guyss, now i distribute your work yaa

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the rest are mine

*if got any problem we can discuss under comment

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hi guyss, now i distribute your work yaa

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hi guyss, now i distribute your work yaa

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these three questions are for Hakim

*if got any problem we can discuss under comment

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My name is T’ng Yi Qi can call me YiQi

My matric no is 302170 from Bachelor of Operations Management

I’m from Pulau Pinang BukitMertajam, a place full with warm heart people and delicious food😋

My inasis is TNB ⚡️

Lastly my phone number is 01126822929📱