Answer : Objective
Note : In the linear programming model, objective component represents the affect of decision variable upon the value and cost while determining the performance of the variables as constraints and objective functions effect changes that happens to one component as they are proportional to its magnitude.
Which of the following components of a linear programming model is the overall performance measure? Multiple...
Solve the following model using linear programming (allow for continuous values and determine the values of the decision variables and objective function. Then, round the decision variables values down to the nearest integer and determine the value of the decision variables and objective function, this is an approximate answer to solving the model using integer programming. Observe if the rounding provides a "feasible solution, all constraints are satisfied. Finally, solve the model using integer programming and determine the values of...
You are given the following linear programming model in algebraic form, where x1and x2are the decision variables and Zis the value of the overall measure of performance. Maximize Z= 20x1+ 10x2 subject to x1- x2 ≤ 1 3x1+ x2 ≤ 7 And x1≥ 0 x2≥ 0 Use the graphical method to solve this model.
Define: a. Model, Variables, Parameters b. Constraints in linear programming c. Mathematical relationships known with certainty and probabilistic conditions(risk model)
Create a worksheet called "Transport a. Enter the following transportation model into excel following the linear programming layout. Hint: this is unbalanced Make sure to include your 1) decision variables, 2) objective function, 3) constraints, 4) inequalities, 5) confounds, 6) and solution b. c. Once you run your model, select "keep solver solution". Name the sheet that's created "solution_basic" DESTINATIONS 13 20 20 25 10 12 30 16 35 20 30 25
Consider the following simple linear regression model: y=Po+P1x Po and B1 are Multiple Choice 41 the response variables the random error terms the unknown parameters the explanatory variables 11 of 30 Prev Next
QUESTION 20 In what parts of a linear programming formulation do the decision variables appear? In the objective function only In the RHS of constraints only In the LHS of constraints only Can appear in both RHS and LHS of constraints AND the objective function None are correct QUESTION 21 A constraint that directly affects the optimal solution in a linear program is called A non-binding constraint A null constraint A binding constraint None of the above QUESTION 22 Which...
Consider the following linear programming model. Formulate an equivalent model with one less constraint ( other than the constraints of non-negativity). Max 7x + 5y Constraints 4x + 3 y <= 2400 2x + 0.5y <= 750 x >= 100 x,y >= 0
perfecting a rich decision-making background, modeling with actual simulation data, and solving (mainly linear programming models and SPREADSHEET solutions). It is sufficient to create a large linear programming model. If necessary, individual small models can be added, but on the premise of better problem solving, the content cannot be split to destroy the overall unity. criteria: degree of innovation in specific topic selection, rationality of model background and amount of information, richness of model description and setting (type and number...
Question 11 an assignment problem is a special type of transportation problem. True False Question 12 when formulating a linear programming problem on a spreadsheet, the data cells will show the optimal solution. True False Question 13 an example of a decision variable in a linear programming problem is profit maximization. True False Question 14 Predictive analytics is the process of using data to. C) determine the break-even point. D) solve linear programming problems. B) predict what will happen in...
Assignment 1. Linear Programming Case Study Your instructor will assign a linear programming project for this assignment according to the following specifications. It will be a problem with at least three (3) constraints and at least two (2) decision variables. The problem will be bounded and feasible. It will also have a single optimum solution (in other words, it won’t have alternate optimal solutions). The problem will also include a component that involves sensitivity analysis and the use of the...