1. (5 points) Formulate and solve Glickman Electronics from page 701 in the textbook. Use the layout used in the video. a. What is the final value of the objective function? b. What are the values of the decision variables? 0. Which constraints are binding? d. What would you pay to relax each constraint? Glickman Electronics Example The Glickman Electronics Company in Washington, DC, produces two products: (1) the Glickman x-pod and (2) the Glickman BlueBerry. The production process for each product is similar in that both require a certain number of hours of electronic work and a certain number of labor-hours in the assembly department. Each X-pod takes 4 hours of electronic work and 2 hours in the assembly shop. Each BlueBerry requires 3 hours in electronics and 1 hour in assembly. During the current production period, 240 hours of electronic time are available, and 100 hours of assembly department time are available. Each x-pod sold yields a profit of $7; each BlueBerry produced may be sold for a $5 profit. Glickman's problem is to determine the best possible combination of x-pods and BlueBerrys to manufacture to reach the maximum profit. This product-mix situation can be formulated as a linear programming problem. We begin by summarizing the information needed to formulate and solve this problem (see Table B.1). Further, let's introduce some simple notation for use in the objective function and constraints. Let: Xi = number of x-pods to be produced X2 = number of BlueBerrys to be produced = TABLE B.1 Glickman Electronics Company Problem Data HOURS REQUIRED TO PRODUCE ONE UNIT X-PODS (X) BLUEBERRYS (X) 4 3 DEPARTMENT Electronic Assembly Profit per unit AVAILABLE HOURS THIS WEEK 240 100 2 1 $7 $5 81% Page 701 of 808 . Location 18498 of 23024 Variables X-pods: Blueberrys: Objective Function Max Profit = 7*X + 5*B Constraints Electronics: 4*X + 3*B = 240 Assembly: 2*X + 1*B S 100 X20: X 20 B 20: B 20