A Carbon Aware Ant Colony System (CAACS)

TL;DR

This paper presents CAACS, a novel ant colony algorithm designed to solve the GTSP by minimizing carbon emissions alongside traditional objectives, promoting sustainable transportation solutions.

Contribution

The paper introduces a bi-objective ant colony system that incorporates carbon emission minimization into route optimization for the first time.

Findings

Effective in balancing environmental and economic objectives.

Reduces carbon emissions in transportation routing.

Applicable to real-world logistics problems.

Abstract

In an era where sustainability is becoming increasingly crucial, we introduce a new Carbon-Aware Ant Colony System (CAACS) Algorithm that addresses the Generalized Traveling Salesman Problem (GTSP) while minimizing carbon emissions. This novel approach leverages the natural efficiency of ant colony pheromone trails to find optimal routes, balancing both environmental and economic objectives. By integrating sustainability into transportation models, CAACS provides a powerful tool for real-world applications, including network design, delivery route planning, and commercial aircraft logistics. Our algorithm's unique bi-objective optimization advances the study of sustainable transportation solutions.