6Efficient-driven Approaches Related to Meta-Heuristic Algorithms using Machine Learning Techniques
Ashima Arya, Swasti Singhal, and Rashika Bangroo
Department of Computer Science and Information Technology, KIET Group of Institutions, Ghaziabad, Uttar Pradesh, India
6.1 Introduction
The optimization approach is a vital tool that may be used to acquire the design parameters that are sought as well as the optimal operating circumstances. This would provide direction for the experimental effort and lessen the risks as well as the costs associated with designing and managing the system. Optimization is the process of identifying the values of the decision variables that produce the highest or lowest value of one or more desired outcomes. The design of objective functions and the optimization approach that is chosen both have a role in determining the reliability of optimal solutions. For optimization, a mathematical model is required that both describes and analyses the behavior of the mechanism. When dealing with complicated nonlinear systems, optimization search may be able to assist in the estimation of unknown parameters. In dynamic processes, robust optimization might be used to find the uncertainty variables. The approach of scale-up and the design of multiphase reactors and flow systems might both benefit from the application of optimization as a tool. Manufacturing and engineering activities will not have the same level of efficiency that they do right now if the designs ...
Get Meta-Heuristic Algorithms for Advanced Distributed Systems now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.