Assignment Brief/ Coursework Content: The coursework is based on the application of linear programming technique to develop, model, formulate, and solve a problem based on the context given below in the assessment body (using Graphical Method). The assignment covers the Learning Outcomes - 1, 3, 4. Students should develop/build mathematical models and show a theoretical understanding of the mathematical formulation of model on the context given below. Evaluate and present critical analyses of modelling output and its practical implications. Students need to develop a model and proceed further with all the tasks stated below.

Task 1 A). Design and model an objective of your problem. Decide on minimization or maximization for the problem you are modelling. After understanding the conditions of the problem, develop a decision model that has (2 variables) and 4 constraints (could be more if needed) relevant to your problem, assume all the necessary values that you shall require. After writing down the expressions of your model, solve it using Graphical Method.

Task 1 B). Later, select any one of the constraints that contributes to the Z function (i.e., the objective function) optimality. Increase and decrease 1 unit on the R.H.S (resource) and find how the constraint line deviates and the point of intersection if any. Mention the shadow price value (if any). Draw both the lines using graph sheet for the increase and decrease.

Task 1 C). Select any one of the coefficient values of Z function. Increase and decrease by 1 unit and draw changes in position of the respective Z lines for each one of them.

Task 1 D Present your shadow price (if any) and the binding and non-binding constraints in your problem, (if any). Critically analyse the impact of changing R.H.S of the constraint on the objective function and the coefficient of the Z function on the constraints. -If you dont get a shadow price, please explain these terminologies (shadow price, binding and non-binding constraints, feasible limits, and applications and benefits of sensitivity analysis).