Solve Multi-Objective Optimization Problems Using GA Solver in Matlab

Hello everyone!

In this video, I’m going to show you a simple but effective way to solve various multi-objective optimization problems.

This approach is very easy to implement, and it is based on multi-objective genetic algorithm solver (multi-objective GA solver) in Matlab.

Multi-objective optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, multiattribute optimization or Pareto optimization) is an area of multiple criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Multi-objective optimization has been applied in many fields of science, including engineering, economics and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conflicting objectives. Minimizing cost while maximizing comfort while buying a car, and maximizing performance whilst minimizing fuel consumption and emission of pollutants of a vehicle are examples of multi-objective optimization problems involving two and three objectives, respectively. In practical problems, there can be more than three objectives (wikipedia.org)

Here are the details of the multi-objective optimization problem to be solved in this video.

Let’s see how to use this optimization solver to solve a simple multi-objective optimization problem.

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