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        MGMT20005代寫、c/c++,Python程序代做
        MGMT20005代寫、c/c++,Python程序代做

        時(shí)間:2024-09-09  來源:合肥網(wǎng)hfw.cc  作者:hfw.cc 我要糾錯(cuò)



        MGMT20005 Business Decision Analysis Lecture 1 
         Before/after tutorials – by email appointment

        Teaching Team 3  “A practical subject, focuses more on practice than theory” ? “I enjoyed learning about aspects and problems that we can see and apply to

        situations we may experience and see happening in the world. This was in particular

        with the linear programming with learning about how it can be used to solve real

        problems” ? “I liked that almost everything we learnt has practical applications, such as LP and

        decision trees.”

         This is a practice-oriented subject.

        Feedback from Previous Students 4 ?Why BDA?

         Hone your analytical skills ? Improve your problem solving capabilities

         Make better decisions

         … Importance of This Subject Data Information Insights Decisions 5 BDA STARTS AFTER UNCOVERING INSIGHTS IN DATA… You need to ACT on the insights and make some DECISIONS that ADD-VALUE to the bottom line! ?Analytics is everywhere. It is no longer a nice-to-have.
         Marketing, finance, operations, health care, sports et al.

         We will draw heavily on examples from different disciplines including marketing, accounting,

        operations and finance.

        Importance of This Subject 6 Three Types of Analytics 7 ?Deterministic models: All relevant data are known with certainty. The decision maker needs

        to identify the optimal decision within the constraints. Techniques include: ? Linear Programming (LP) ? Integer Linear Programming (ILP) ? Non-Linear Programming (NLP) ?Stochastic models: Some data are uncertain. The probability concept is used. Techniques

        include: ? Decision Tree Analysis and Utility Model ? Simulation-based Optimisation

         Scenario Analysis and Robust Optimisation ? Stochastic Dynamic Programming ? Stochastic Linear Programming ? Stochastic Integer Programming ? Markov Chain Process ? Queuing Models Types of Decision Models 8 Introduction to BDA and Decision AnalysisWeek 1 Decision Making under RiskWeek 2 Value of InformationWeek 3 Multi-Criteria Decision MakingWeek 4 Deterministic Optimisation Introduction to Linear Programming (LP)Week 5 Sensitivity Analysis in LPWeek 6 LP ApplicationsWeek 7 Network ModelsWeek 8 IP ApplicationsWeek 9 Monte Carlo SimulationWeek 10 Simulation-based OptimisationWeek 11 Simulation Modelling Review and RevisionWeek 12 Decision Analysis 9 Subject Contents Anderson, D.R., Sweeney, D.J., Williams, T.A., Camm, J.D., & Martin, K. (2019), An Introduction to Management Science: Quantitative Approaches to Decision Making, 16th edition, South-Western Cengage Learning ? You can borrow the ebook/hard copy from the library. ? You can purchase the hard copies in Co-op or from Cengage website . The publisher also offers e-Books and e-Chapters with cheaper prices. - Discount code: WOW10 - Previous versions also work. 10 Prescribed Textbooks ? Excel Solver: Spreadsheets are the tool of choice for today’s managers. ? Other (optional): ? SAS/OR ? LINDO ? MATLAB optimization package ? R with Gurobi package ? Gurobi ? CPLEX ? Arena Simulation Software Software 11 ? Learning materials: ? Pre-lecture study ? Lecture slides ? Text book ? Tutorial questions ? Class and tutorials ? Lecture (1 hour theory + 1 hour case study or

        application/exercises) ? Tutorial session (1 hour) workshop with Excel ? Post-lecture, summary and quiz ? Peer learning ? Perusall ? Assessment Pre- Reading Learning

        material CLASS Peer

        learning Assessment Study/Learning Format 12 ? A Quantitative Subject ? Read, think, practice ? Class exercises ? Rule of thumb + Analytical mindset!! ? Assessments ? Assignment 1 (25%): An individual assignment on decision analysis ? Assignment 2 (25%): A 2500-word group assignment on optimization
         Exam (50%): An open book final examination , NO hurdle requirement Studying for MGMT20005 13 The assignment will involve using the decision analysis models discussed in lectures to solve decision-making problems that arise in the business world. The assignments will involve analysis of model using computer tools, as well as drawing on more theoretical materials from lectures. ? Materials from weeks **4 ? Submission: Canvas assignment ? Time limit: Once you start the Assignment, you will have 140 minutes to complete and submit

        it. However, you can start working on this assignment any time during the time window (e.g.,

        Monday to Friday) ? Due date: Week 5, Friday 6 pm Individual Assignment (25%) 14 The group assignment is designed to allow you to demonstrate that you can effectively formulate and analyse business decision problems, apply mathematical modelling approaches such as LP or IP to solve the problems. You must master Excel Solver to obtain an optimal solution, generate a sensitivity analysis report, and suggest courses of action for management. You can choose the group to join (from the same tutor/tutorial group). Contribution of each team member required to be clearly attributed. ? Materials from weeks 5-10 ? Group Assignment: Form a team of up to 3 students by yourself ? Word limit: 2500 ? Due date: Week 11, Friday 6pm Group Assignment (25%) 15 ? This is a two-hour open book exam covering all topics taught in the lectures/tutorials.

         You can bring 2 double-sided A4 pages (handwritten or printed) to the exam venue. ? It consists of questions like the worked examples in lectures and tutorials.

         Scientific calculators are allowed.

         During the Examination Period. End-of-Semester Exam (50%)

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