Feedback Searching Bias and Measurement of its Effect on Ant Colony Optimization

Abstract

One of the obstacles in applying ant colony optimization (ACO) to the combinatorial optimization is that the search process is sometimes biased by algorithm features such as the pheromone model and the solution construction process. Due to such searching bias, ant colony optimization cannot converge to the optimal solution for some problems. In this paper, we discover and define a new type of searching bias in ACO named feedback bias. We empirically prove the existence of feedback bias and its influence on ACO. We also present the concept of intensity of bias as a measurement of the effect on ACO by such bias. Our experimental results show that it is reasonable and reliable to use the intensity to measure the influence of bias on ACO.