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In the second case, the constrains of customer demand and truck capacity are furtherconsidered to make the scenario more practical. Hence, capacities of these 3 self-pickuptrucks are given on Table 2(a) and the locations and demands of 30 customers areshown on Table 2(b). You are required to solve the below optimization problem byusing MS Excel Solver to provide instruction to the transportation team.Table 2(a). List of truck locationsSelf-pickupTruckLocation Capacity(in kg)X YTruck A 1 1 50Truck B 10 10 80Truck C 20 20 80Total = 210 kgTable 2(b). List of customer locationsCustomer Location Demand(in kg) Customer Location Demand(in kg) Customer Location Demand(in kg)X Y X Y X YC1 1 3 4.5 C11 16 12 7.5 C21 31 25 2C2 2 35 5 C12 17 32 6.5 C22 31 35 5C3 5 5 8 C13 18 17 5 C23 31 44 8C4 5 47 6.5 C14 21 33 7.5 C24 37 42 6.5C5 5 17 6.5 C15 22 12 8 C25 38 6 4.5C6 9 5 4.5 C16 24 27 9.5 C26 42 41 5.5C7 10 19 7.5 C17 24 8 7.5 C27 42 49 8C8 11 43 8 C18 27 37 9.5 C28 42 7 7.5C9 13 25 7.5 C19 28 12 4.5 C29 47 26 4.5C10 15 45 5 C20 29 8 9.5 C30 49 8 6.5Report preparation (in Word):1. The mathematical model of the above problem with descriptions2. Screen captures of your settings in (i) Excel sheet(s) and (ii) Solver withdescriptions3. Visualization of (i) the optimal truck locations with customer locations and (ii)optimal total travelling distanceSubmit your report about the above tasks in ONE file in .doc/.docx/.pdf. Pleasename the file with your student ID, e.g. 12345678d-ASM1.doc/.docx/.pdf.Submission Deadline: The end of the day of 29 September 2023 (Week 4)

Question

In the second case, the constrains of customer demand and truck capacity are furtherconsidered to make the scenario more practical. Hence, capacities of these 3 self-pickuptrucks are given on Table 2(a) and the locations and demands of 30 customers areshown on Table 2(b). You are required to solve the below optimization problem byusing MS Excel Solver to provide instruction to the transportation team.Table 2(a). List of truck locationsSelf-pickupTruckLocation Capacity(in kg)X YTruck A 1 1 50Truck B 10 10 80Truck C 20 20 80Total = 210 kgTable 2(b). List of customer locationsCustomer Location Demand(in kg) Customer Location Demand(in kg) Customer Location Demand(in kg)X Y X Y X YC1 1 3 4.5 C11 16 12 7.5 C21 31 25 2C2 2 35 5 C12 17 32 6.5 C22 31 35 5C3 5 5 8 C13 18 17 5 C23 31 44 8C4 5 47 6.5 C14 21 33 7.5 C24 37 42 6.5C5 5 17 6.5 C15 22 12 8 C25 38 6 4.5C6 9 5 4.5 C16 24 27 9.5 C26 42 41 5.5C7 10 19 7.5 C17 24 8 7.5 C27 42 49 8C8 11 43 8 C18 27 37 9.5 C28 42 7 7.5C9 13 25 7.5 C19 28 12 4.5 C29 47 26 4.5C10 15 45 5 C20 29 8 9.5 C30 49 8 6.5Report preparation (in Word):1. The mathematical model of the above problem with descriptions2. Screen captures of your settings in (i) Excel sheet(s) and (ii) Solver withdescriptions3. Visualization of (i) the optimal truck locations with customer locations and (ii)optimal total travelling distanceSubmit your report about the above tasks in ONE file in .doc/.docx/.pdf. Pleasename the file with your student ID, e.g. 12345678d-ASM1.doc/.docx/.pdf.Submission Deadline: The end of the day of 29 September 2023 (Week 4)

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Solution

Sure, I can help you with that. Here's a step-by-step guide on how to solve the optimization problem using MS Excel Solver:

  1. Mathematical Model: The problem can be modeled as a Vehicle Routing Problem (VRP). The objective is to minimize the total traveling distance of all trucks, subject to the constraints that each customer is visited by exactly one truck and the total demand of each truck does not exceed its capacity.

  2. Excel Sheet Settings:

    • Create a distance matrix that calculates the Euclidean distance between each pair of locations (trucks and customers).
    • Create a decision variable matrix that indicates whether a truck travels from one location to another.
    • Calculate the total traveling distance of each truck by summing the product of the distance and decision variable matrices.
    • Calculate the total demand of each truck by summing the product of the demand and decision variable matrices.
  3. Solver Settings:

    • Set the objective to minimize the sum of the total traveling distances of all trucks.
    • Add constraints that the sum of the decision variables for each customer equals 1 (each customer is visited by exactly one truck).
    • Add constraints that the total demand of each truck does not exceed its capacity.
    • Set the decision variables to binary.
  4. Visualization:

    • Plot the optimal truck locations and customer locations on a scatter plot.
    • Draw lines between the locations to represent the optimal routes.
  5. Report Preparation:

    • Write a description of the mathematical model.
    • Take screen captures of your Excel sheet and Solver settings.
    • Include the visualization in your report.

Remember to save your report as a .doc, .docx, or .pdf file and name it with your student ID. The deadline for submission is the end of the day on 29 September 2023.

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