#multi-objective optimization

Scalarizing multi-objective optimization problems: Method comparison

I already introduced various coding examples implementing multi-objective optimization. In these examples I implemented different strategies for searching a multi-objective optimum. One of these strategies was based on scalarizing multiple objectives into a single objective function using weights for each indivual objective function. In this article I want to provide a more comprehensive…

The Pareto Principle And Pareto Analysis In A Nutshell

The Pareto Analysis is a statistical analysis used in business decision making that identifies a certain number of input factors that have the greatest impact on income. It is based on the similarly named Pareto Principle, which states that 80% of the effect of something can be attributed to just 20% of the drivers.

Understanding the Pareto Analysis

The Pareto Analysis was named after…

Multi-objective linear optimization with weighted sub-problems, using PuLP in Python

In my most recent post on linear programming I applied PuLP for solving below linear optimization problem, using two approaches. Approach #1 was based on solving a sub-problem with one objective only first, then adding the optimal outcome of that problem to a second sub-problem that considered objective two only. Approach #2 is based on combining all objectives into one overall objective…

Things to Consider When Performing Multidisciplinary Optimization Projects