Combinatorial Optimization

Chapter
Part of the Decision Engineering book series (DECENGIN, volume 0)

Abstract

Previous chapters discuss parameter optimization, i.e., we need to find the optimal values of variables so that the objective function has the maximum/minimum value. Many real-world problems are not like this. We often need to select some elements from a set or arrange the sequence of some events with constraints so that the objective function has the maximum/minimum value. These problems belong to combinatorial optimization. We will introduce three examples, explain their respective properties, illustrate how EAs solve them, and summarize design-effective algorithms for them.

Keywords

Travel Salesman Problem Travel Salesman Problem Knapsack Problem Hamiltonian Cycle Active Schedule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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