Optimization Problems and Algorithms

OCW Scholar

« Previous | Next »

Session Overview

Photograph of a backpack.

This lecture continues the discussion of curve fitting, emphasizing the interplay among theory, experimentation, and computation and addressing the problem of over-fitting. It then moves on to introduce the notion of an optimization problem, and illustrates it using the 0/1 knapsack problem.

Image courtesy of kob42kob on Flickr.

Session Activities

Lecture Videos

About this Video

Topics covered: Modeling, optimization, greedy algorithms, 0-1 knapsack problem.


Check Yourself

What does an optimization problem consist of?

View/hide answer

An optimization problem requires that an objective function be optimized, either by maximizing or minimizing the function. There may also be a set of constraints that must be accounted for.



What is problem reduction?

View/hide answer

Taking a problem with an unknown solution and reducing it to a problem or problems with known solutions.



Problem Sets

Problem Set 8: Simulating The Spread of Disease and Virus Population (Due)

In this problem set, using Python and pylab you will design and implement a stochastic simulation of patient and virus population dynamics, and reach conclusions about treatment regimens based on the simulation results.

Problem Set 9 (Assigned)

Problem set 9 is assigned in this session. The instructions and solutions can be found on the session page where it is due, Lecture 20 More Clustering.


« Previous | Next »