Efficiency analysis of the Ant System algorithm on the Flow Shop Scheduling Problem

Abstract

This article analyzes the effectiveness of the Ant System (AS) on the benchmark dataset of a production scheduling task, the Flow Shop Scheduling Problem (FSS). The Ant System (AS) algorithm is one of the algorithms of the Ant Colony Optimization (ACO) family, which is based on the behavior of ants. This is a population algorithm that iteratively improves individual elements of the population until the stopping condition is met. Flow Shop Scheduling is a task in which specific jobs must be performed on specific machines and the goal is to minimize the makespan. The article presents the FSS task, the AS algorithm, and the methods used for efficiency analyses. The tests showed that the Ant System algorithm is effective for the Flow Shop Scheduling task as a discrete production scheduling task.