Abstract
Before we move on to the discussion of metaheuristic algorithms, a brief overview is given in this chapter to make it clear what an optimization problem is. It begins with the general definition of an optimization problem that is composed of the objective function, constraint, and solution. The most widely known problems are certainly the so-called combinatorial and continuous optimization problems. The combinatorial optimization problems described herein include the one-max, 0-1 knapsack, binary to decimal, and traveling salesman problems, whereas the continuous optimization problems described herein include the so-called single-objective and multi-objective optimization problems. In addition to the definitions, the landscape of the solution space of these optimization problems is also given to show their distinguishing features.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
