Behavioral Strategy in Perspective by Augier Mie;Fang Christina;Rindova Violina;

Author:Augier, Mie;Fang, Christina;Rindova, Violina;
Language: eng
Format: epub
Publisher: Emerald Publishing Limited
Published: 2018-09-07T00:00:00+00:00

Some Simplified Concepts of Intractability from Computational Complexity

The purpose of this section is to introduce some simplified concepts from computational complexity. We do not introduce the vast majority of concepts in this theory, nor do we rigorously discuss what we do address. We introduce only what is necessary to draw some interesting conclusions about computational, managerial, and organizational intelligence; and to provide enough understanding for interested readers to pursue computational complexity deeper, if they so desire. Specifically, we discuss how computational complexity generally approaches intractability due to limits on computational speed (and thus processing time).

We start with a brief discussion of two different types of functions that are important to computational complexity. Let “n” represent the size of the input to a computer program. In the TSP examples above, n = 100 for the first, n = 48 for the second, and n = 1,000 for the third. The first type of function involves polynomial terms such as n2, n3, or n5 that are commonly studied in algebra classes before high school. The second class, “exponential” functions such as 2n are not as common till later in education, but important for understanding of computational complexity. Table 1 shows how polynomial, exponential, and some other super polynomial functions increase for increasing levels of input size, “n”.

Table 1. Polynomial and Super Polynomial Functions.

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