Untitled UNIVERSITY OF ECONOMICS HO CHI MINH CITY FACULTY OF INTERNATIONAL BUSINESS MARKETING FINAL NON PRESENTATION INDIVIDUAL PROJECT BUSINESS MODELING AND APPLICATIONS oOo Name of Lecturer Nguy[.]
lOMoARcPSD|17838488 UNIVERSITY OF ECONOMICS HO CHI MINH CITY FACULTY OF INTERNATIONAL BUSINESS - MARKETING FINAL NON-PRESENTATION INDIVIDUAL PROJECT BUSINESS MODELING AND APPLICATIONS oOo Name of Lecturer: Nguyen Thi Hong Thu Subject code: 22C1BUS50321204 Student ID: 31211020894 Student name: Truong Dang Hong Duong Course – Class: K47 – FTC01 lOMoARcPSD|17838488 Date: 22 December, 2022 University of Economics Ho Chi Minh city Faculty of International Business - Marketing Business Modeling and Applications Final Non-Presentation Individual Project Subject Code: 22C1BUS50321204 Subject Name: Business Modeling and Applications Lecturer Name: Nguyễn Thị Hồng Nhung Student Name: Trương Đặng Hồng Dương Student ID: 31211020894 Date: 22 December, 2022 lOMoARcPSD|17838488 Endorsement The author of this essay, Truong Dang Hong Duong, asserts that it was a personal undertaking overseen by my course instructor, Ms Nguyen Thi Hong Nhung All of the research and writing in this document is based on my own knowledge that I learned from the instructor I certify that neither other people's nor other organizations' work was used to create this publication The information in this post was individually gathered, examined, and summarized using Excel Solver and QM for Windows If any fraud is discovered in this article notwithstanding the claims made above, I shall be entirely liable for its content Thursday, 22 December 2022 Author (Signed) Truong Dang Hong Duong lOMoARcPSD|17838488 Lecturer’s Comment lOMoARcPSD|17838488 Table of Content Endorsement Lecturer’s Comment Table of Content Main Content Linear Programming Decision making Forecasting 5 14 16 References Appendix 21 22 lOMoARcPSD|17838488 MAIN CONTENT Linear Programming (05 Pts) Imagine a similar problem and analyze it: HD is a company that creates public services for its community It has six consultants and eight clients on board for the project Because the consultants have varying technical abilities and experience, the company charges different hourly rates for its services Furthermore, some consultants' skills are better suited for certain projects than others, and clients may prefer one consultant over another A consultant's suitability for a project is graded on a 5-point scale, with being the worst and being the best The table below shows each consultant's rating for each project, as well as the hours available for each consultant, as well as the contracted hours and maximum budget for each project: Project Consultant Hourly wage Available hours A $150 3 5 3 3 450 B $140 3 5 3 600 C $160 3 500 D $300 1 2 300 E $270 1 2 3 710 F $150 3 3 860 500 240 400 475 350 460 290 200 100 80 120 90 65 85 50 55 Project Hours Contract budget (x1000 USD) lOMoARcPSD|17838488 The company wants to know how many hours each consultant should be assigned to each project in order to best utilize their skills while meeting the needs of the clients a Formulate a linear programming model and write down the mathematical model for this problem To formulate a linear programming model, I need to know: The number of hours assigned to a consultant to take responsibility for a project is one of the decisive variables: xiy: The hours that Consultants are assigned to project In that: i= A, B, C, D, E, F is Consultant y= 1, 2, 3, 4, 5, 6, 7, is Project The final goal is to make use of the abilities of the consultants based on their rank It means UTC wants to maximize the hours that are specified and rated The points the higher the better (from to 5) The Available hours as a table below: The same with Project hours: lOMoARcPSD|17838488 And The Contract budget Downloaded by hây hay (vuchinhhp3@gmail.com) lOMoARcPSD|17838488 The number of hours that they consult per project: xiy ≥ If I apply the mathematical models to solve this problem: First, I need to define the variables as shown in the table below: A1, A2, A8 Hours that Consultant A is assigned to Project 1, 2, , B1, B2, B8 Hours that Consultant A is assigned to Project 1, 2, , C1, C2, C8 Hours that Consultant A is assigned to Project 1, 2, , D1, D2, D8 Hours that Consultant A is assigned to Project 1, 2, , E1, E2, E8 Hours that Consultant A is assigned to Project 1, 2, , 8 Downloaded by hây hay (vuchinhhp3@gmail.com) lOMoARcPSD|17838488 F1, F2, F8 Hours that Consultant A is assigned to Project 1, 2, , The following formula can be used to calculate the objective or total suitability: 3A1+3A2+5A3+5A4+3A5+3A6+3A7+3A8+3B1+3B2+2B3+5B4+5B5+5B6+3B7+3B8+2C1+C2+3 C3+3C4+2C5+C6+5C7+3C8+D1+3D2+D3+D4+2D5+2D6+5D7+D8+3E1+E2+E3+2E4+2E5+3E6 +3E7+3E8+4F1+5F2+3F3+2F4+3F5+4F6+3F7+3F8 Constraints: Constraints 1: The total hours of Consultant need to be ≤ The Available hours A1+A2+A3+A4+A5+A6+A7+A8 ≤ 450 B1+B2+B3+B4+B5+B6+B7+B8 ≤ 600 C1+C2+C3+C4+C5+C6+C7+C8 ≤ 500 D1+D2+D3+D4+D5+D6+D7+D8 ≤ 300 E1+E2+E3+E4+E5+E6+E7+E8 ≤ 710 F1+F2+F3+F4+F5+F6+F7+F8 ≤ 860 Constraints 2: The total hours per Project is equal to the Project hours A1+B1+C1+D1+E1+F1 = 500 A2+B2+C2+D2+E2+F2 = 240 A3+B3+C3+D3+E3+F3 = 400 A4+B4+C4+D4+E4+F4 = 475 A5+B5+C5+D5+E5+F5 = 350 A6+B6+C6+D6+E6+F6 = 460 A7+B7+C7+D7+E7+F7 = 290 Downloaded by hây hay (vuchinhhp3@gmail.com) lOMoARcPSD|17838488 Based on this information, Petrolimex can make decision to offer the local company to open a new dealership It can be explained that in options, Petrolimex has, the local company reach the highest expectation – salvage – value In other hand, EMV cannot completely guarantee that the decision can be made Forecasting (02 Pts) Fill the monthly demand of a water bottle extracted from a supermarket data to the following table Month Demand 50000 30000 20000 10000 60000 70000 80000 90000 50000 10 30000 11 20000 12 10000 a Using averaging forecasting method, calculate the forecast This method uses all the data points in the time series and simply averages them Thus, the forecast of what the next data point will turn out to be is: Forecast = Average of all data to date I have applied this method to solve the problem, which is represented in my Excel file: 16 Downloaded by hây hay (vuchinhhp3@gmail.com) lOMoARcPSD|17838488 b Using 3-month moving average forecasting method (n=3), calculate the forecast The moving average method forecasts for the next period by taking the average of the n nearest values in a time series The 3-month moving average method is to take the average result of the data from the last months to find a forecast for the next month Applying the 3-period moving average method to the data of October, November, and December, we have a forecast of the supermarket's bottled water demand in the next June as follows: Conclusion: From the data calculated using the 3-period moving average method and the demand in the last months (30000, 20000, and 10000), we have a forecast report for the industry manager In the next June, supermarkets purchased 20,000 bottles of bottled water I also use Excel to represent this method: 17 Downloaded by hây hay (vuchinhhp3@gmail.com) lOMoARcPSD|17838488 c Using last-value forecasting method, calculate the forecast The last-value forecasting method ignores all the data points in a time series except the last one It then uses this last value as the forecast of what the next data point will turn out to be, so the formula is simply: Forecast = Last value Applying this formula and calculating the forecasting error, MAD, MSE we have the result as following: 18 Downloaded by hây hay (vuchinhhp3@gmail.com) lOMoARcPSD|17838488 d Explain methods of forecast Which one is better and more accurate according to you? You can explain however you want In my perspective, MAD and MSE are common measures of forecast accuracy To find the more accurate forecasting model, forecast with each tool for several periods where the demand outcome is known, and calculate MSE and/or MAD for each The smaller error indicates the better forecast (Timeseries forecasting, moderate) So according to the results we got, it is obvious that the 3-period moving average is the best of the three Furthermore, based on the theory, other two methods seem to embrace some limits: The averaging forecasting method: The estimate is excellent if the process is entirely stable, i.e., if the assumptions about the underlying model are correct However, frequently, there is skepticism about the persistence of the underlying model over an extended period of time Conditions inevitably change eventually Because of a natural reluctance to use very old data, this procedure generally is limited to young processes 19 Downloaded by hây hay (vuchinhhp3@gmail.com) ... International Business - Marketing Business Modeling and Applications Final Non- Presentation Individual Project Subject Code: 22C1BUS50321204 Subject Name: Business Modeling and Applications Lecturer... hours of each project: I have projects, which leads to constraints: Hours of Project 1, 2, 3… - The revenue of each project, as well as the hours for each project, I have: Revenue Project 1, 2,... of each consultant, The hours of each project and revenue from each project: - Each consultant’s availability: I have six consultants named A, B, C, D, E and F So that I also have available hours