學門類別
哈佛
- General Management
- Marketing
- Entrepreneurship
- International Business
- Accounting
- Finance
- Operations Management
- Strategy
- Human Resource Management
- Social Enterprise
- Business Ethics
- Organizational Behavior
- Information Technology
- Negotiation
- Business & Government Relations
- Service Management
- Sales
- Economics
- Teaching & the Case Method
最新個案
- A practical guide to SEC ï¬nancial reporting and disclosures for successful regulatory crowdfunding
- Quality shareholders versus transient investors: The alarming case of product recalls
- The Health Equity Accelerator at Boston Medical Center
- Monosha Biotech: Growth Challenges of a Social Enterprise Brand
- Assessing the Value of Unifying and De-duplicating Customer Data, Spreadsheet Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise, Data Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise
- Board Director Dilemmas: The Tradeoffs of Board Selection
- Barbie: Reviving a Cultural Icon at Mattel (Abridged)
- Happiness Capital: A Hundred-Year-Old Family Business's Quest to Create Happiness
Optimization Modeling Exercises
內容大綱
The problem set contains three problems designed to help students practice their ability to build math programming models. Problem # 1 is a portfolio problem where the student is asked to find a portfolio that minimizes risk (variance) subject to a required rate of return; as such, it is nonlinear. Problem # 2 is aggregate production scheduling; hence, linear. Problem # 3 involves determining how to source a fixed quantity from a menu of vendors with differing fixed- ordering charges and per-unit prices; it is a mixed integer model. All are sufficiently small that they can be easily optimized with standard math programming software (such as Excel's standard Solver).