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MANAGEMENT SCIENCE 461

MANAGEMENT SCIENCE 461. Lecture 1a – Introduction September 9, 2008. Contact Information. Chris Neuman Phone 442-6426 Email 1: cneuman@ualberta.ca Office: Shadowy and Vague Office hours: By appointment (after 4:30) Intros…. Website. https://ulearn.ualberta.ca

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MANAGEMENT SCIENCE 461

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  1. MANAGEMENT SCIENCE 461 Lecture 1a – Introduction September 9, 2008

  2. Contact Information Chris Neuman Phone 442-6426 Email 1: cneuman@ualberta.ca Office: Shadowy and Vague Office hours: By appointment (after 4:30) Intros…

  3. Website https://ulearn.ualberta.ca All class material will be posted (spreadsheets, lecture slides, etc) Grade info, digital dropbox, course conferencing

  4. Syllabus Information • Textbook • Classroom • Grading • Homeworks 35% • Quizzes 25% • Project 40%

  5. Homework Policies Code of Student Behaviour Peer help is the best way to learn Discussion of HW problems is healthy and encouraged Just don’t copy each other’s work.

  6. Operations Research The Science of Better Quantitative tools used to make better decisions Broad range of applications, broad range of tools We are specifically addressing …

  7. Distribution Management The process of planning, implementing, and controlling the efficient, effective flow and storage of goods, services, and related information from point of origin to point of consumption for the purpose of conforming to customer requirements. - Council of Logistics Management

  8. DM Cost Drivers • Inventory • Raw materials, WIP, finished goods • Transportation • Carrier selection, shipment size, distance and travel time • Facilities (production and storage) • What? When? Where? Why? • Information • Availability, price, forecasting demand, shipping options

  9. Planning Levels Strategic: long-term, long-range, potentially reshaping the way business is done Tactical: medium-range, designed to raise competitiveness and customer service levels Operational: day-to-day; Efficiency at low cost

  10. Examples • Distribution network configuration • Strategic - a new flow of goods throughout the network • Inventory control • Tactical - determine inventory policy to minimize ordering and holding costs • Crossdocking • Tactical - warehouses serve as coordinators and as transshipment points but do not keep stock themselves

  11. Examples • Integration of inventory and transportation • Tactical - determine balance between inventory and transportation costs • Vehicle fleet management • Operational - assign loads to vehicles and determine vehicle routes

  12. Examples • Truck routing • Operational - determine the minimal length route (time or distance) to follow • Packing problems • Operational - pack items such that the number of bins used is minimized

  13. Trends • Reality: DM problems are computationally intensive, complex, and multi-faceted • Intuition plays a major role in how we approach DM problems • Tools • Descriptive models – what’s happening now? • Prescriptive models – what should we do?

  14. Course focus The focus in this class is on mathematically well-defined problems that can be solved using algorithmic and heuristic techniques IS, outsourcing, 3PL and 4PL, strategic partnerships, B2B and many other buzzwords are difficult to quantify and will be addressed lightly (MGTSC 488)

  15. Dayjet

  16. Why Models? • Reality bites • Data overload, but not information overload • Reliance on computers: Data is masked • Allocation of responsibility (must justify decisions) • Decisions and numbers • Many decisions are numbers • How many distribution centers do we need? • Capacity of new plant? • How many workers assigned to line? • Most decisions depend on numbers • Should we introduce a new product? • Make or buy?

  17. Why Models? • Data + Model = Information • Managers who do not understand models either: • Don’t put faith in analysis, lose valuable information, or • Put too much faith in analysis, are swayed by stacks of computer output

  18. Why Models? Tradeoff analysis Provides a structure for DM Powerful engineering tool, but a key management skill too (re-engineering) Value of model is its usefulness Modeling is an iterative process

  19. Simple algebraic representation

  20. What is xij? Plant 1 Plant 2 Plant 3 Plant 4 Grove 1 Grove 2 Grove 3 x11 x12 x13 x14 x21 x22 x23 x24 X31 x32 x33 x34

  21. More familiar

  22. Solver settings

  23. A Note on Spreadsheets • The good things • Lift the algebraic curtain • Powerful what-if tools • Can analyze, optimize, simulate, build DSS, etc. • 40 million users • One in every office

  24. A Note on Spreadsheets • The bad things • What is a formula, what is data? • What feeds into what? • Scalability: add a product • Dimensionality: add products? Time? • Excel is a powerful tool…but not the answer to every problem

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