October 2024
Intermediate to advanced
412 pages
11h 1m
English
Content preview from Hands-On Prescriptive Analytics
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
Chapter 5. Mathematical Programming: Overview
I will introduce several popular and often used non-stochastic mathematical programming methods for Prescriptive Analytics in this chapter. These are:
-
Classical linear programming
-
Integer programming
-
Mixed programming as a hybrid of the first two
The leading questions for this chapter are:
-
What is the essence of mathematical programming?
-
Why use mathematical programming in Prescriptive Analytics?
-
What is linear programming and what is its use in decision making?
-
What is integer programming and what is its use in decision making?
-
What is mixed programming and what is its use in decision making?
-
How is mathematical programming implemented in Python?
Background
Mathematical programming has a long practical history dating to the 1940s. This broad and powerful tool finds the combination of decision variables that optimizes an objective function. This function could be a production function, for example, based on classical economic theory. The decision variables in this case are capital and labor amounts. See Baumol (1965), Henderson and Quandt (1971), Ferguson (1972), and Gould and Lazear (1989) for economic discussions of production functions.
Optimization means either maximization or minimization, depending on the problem. For example, if the problem is to allocate manufacturing robots (the inputs) to the production of output (the objective function), then this is a maximization problem since you want the most output. ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.