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Empirical study on the effect of population size on MAX-MIN ant system in dynamic environments

Publication Date Jul 1, 2016

Abstract

In this paper, the effect of the population size on the performance of the MAX-MIN ant system for dynamic optimization problems (DOPs) is investigated. DOPs are generated with the dynamic benchmark generator for permutation-encoded problems. In particular, the empirical study investigates: a) possible dependencies of the population size parameter with the dynamic properties of DOPs; b) the effect of the population size with the problem size of the DOP; and c) whether a larger population size with less algorithmic iterations performs better than a smaller population size with more algorithmic iterations given the same computational budget for each environmental change. Our study shows that the population size is sensitive to the magnitude of change of the DOP and less sensitive to the frequency of change and the problem size. It also shows that a longer duration in terms of algorithmic iterations results in a better performance.

Concepts
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Dynamic Optimization Problems
MAX-MIN Ant System
Algorithmic Iterations
Larger Population Size
Smaller Population Size
Effect Of Size
Population Size
Problem Size
Dynamic Environments
Longer Duration

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