Extension of Max-Min Ant System with Exponential Pheromone Deposition Rule

TL;DR

This paper introduces an exponential pheromone deposition rule to enhance the Max-Min Ant System algorithm, demonstrating improved solution quality and faster convergence through theoretical analysis and extensive simulations.

Contribution

It proposes a novel exponential pheromone deposition rule and provides a stability analysis, showing significant performance improvements over traditional uniform deposition methods.

Findings

Exponential deposition outperforms uniform deposition in solution quality.

The new approach converges faster than traditional methods.

Optimal parameter settings enhance the effectiveness of the exponential rule.

Abstract

The paper presents an exponential pheromone deposition approach to improve the performance of classical Ant System algorithm which employs uniform deposition rule. A simplified analysis using differential equations is carried out to study the stability of basic ant system dynamics with both exponential and constant deposition rules. A roadmap of connected cities, where the shortest path between two specified cities are to be found out, is taken as a platform to compare Max-Min Ant System model (an improved and popular model of Ant System algorithm) with exponential and constant deposition rules. Extensive simulations are performed to find the best parameter settings for non-uniform deposition approach and experiments with these parameter settings revealed that the above approach outstripped the traditional one by a large extent in terms of both solution quality and convergence time.