Loading [a11y]/accessibility-menu.js
Basic Notions on Computational Complexity and Approximate Techniques | part of CAD of Circuits and Integrated Systems | Wiley Semiconductors books | IEEE Xplore

Basic Notions on Computational Complexity and Approximate Techniques


Chapter Abstract:

Summary The execution time of a program depends on several factors: program data, quality of the code generated by the compiler, and computational complexity. This chapte...Show More

Chapter Abstract:

Summary

The execution time of a program depends on several factors: program data, quality of the code generated by the compiler, and computational complexity. This chapter begins by examining the simplest class, which includes the polynomial time problems, namely those whose exact solution is obtained within polynomial time. It addresses the choice of developing a heuristic‐ or metaheuristic‐based algorithm. Many optimization problems are related to the graph theory. The modeling of the (non‐polynomial time) problem to be solved makes it possible to choose a heuristic or metaheuristic, whichever is better adapted to the problem at hand. Branch and bound technique involves going through a tree graph in order to reach an optimal or near‐optimal solution. This obviously assumes the avoidance of an exhaustive exploration and making a proper choice at each stage.

Page(s): 1 - 48
Copyright Year: 2020
Edition: 1
ISBN Information:

Contact IEEE to Subscribe