An APIm Algorithm to Solve the Scheduling Problem in an FMS with Presence of Breakdowns

Abstract

Ant colony algorithms are computational methods inspired from the behavior of real ant colonies. In this paper our interest is focused on the adaptation of an optimization algorithm called API based on the foraging behavior model of primitive ants’ population called Pachycondyla apicalis to solve real time alternative routings selection problem in a Flexible Manufacturing System (FMS) with and without presence of breakdowns. The FMS consists of seven machining centers, a loading and an unloading stations, and six different part types. Owing to the presence of identical machining centers, the parts have alternative routings. The scheduling decisions has been established in terms of how the parts are routed through various machines in the system.