Event Phone: 610-715-0115

Cancellation Policy: If you cancel your registration two weeks or more before the course is scheduled to begin, you are entitled to receive your choice of either a credit for a future seminar (which can be applied toward any of our courses) or a refund of the registration fee (minus a processing fee of $50). 

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

A 3-Day Livestream Seminar Taught by Sri Talluri, Ph.D.

This seminar will provide you with a comprehensive understanding of decision analysis tools and their practical application in contemporary business environments. The primary emphasis is on optimization methodologies, which serve as powerful techniques for solving complex managerial and operational problems.

You will gain hands-on experience with a wide range of approaches, including linear and integer optimization, multi-objective optimization, network optimization, and data envelopment analysis. Each method will be contextualized through case applications across diverse domains such as manufacturing systems, financial decision-making, marketing analytics, supply chain management, and transportation and distribution planning.

To ensure both conceptual understanding and practical proficiency, the course incorporates extensive use of spreadsheet-based tools. By the end of the course, you will be well prepared to model, analyze, and solve structured decision problems, bridging the gap between theory and practice.

Here is an example of the kinds of problems that you will learn how to solve in this seminar: A global consumer goods company (e.g., Procter & Gamble or Unilever) produces a range of products—such as shampoo, detergent, and soap—across multiple factories located in different regions. Each product requires specific raw materials that are available in limited quantities. Factories operate under production capacity constraints (e.g., machine hours, labor hours), and some factories are more efficient at producing certain products due to differences in productivity.

The company must meet customer demand for each product across various markets while also accounting for production and transportation costs incurred when producing and shipping products from factories to distribution centers. The goal is to minimize the total costs.

A linear optimization model for this problem would define decision variables as the quantity of each product produced at each factory and the quantity shipped from each factory to each distribution center. The objective function would be to minimize the total cost, while the constraints would include factory production capacity limits, raw material availability, and the requirement to fulfill market demand for each product. The solution to this model would determine the optimal production levels at each plant as well as the shipment quantities from factories to various markets.

Of course, your business problem may be much simpler than this one. But the methods you’ll learn can be applied to both simple and complex problems.