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

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.

Taxonomic revision of the Pachycondyla apicalis species complex (Hymenoptera: Formicidae)

The taxonomy of the Neotropical Pachycondyla apicalis species complex is revised. Contrary to the widely-held view that the apicalis complex contains only two species, P. apicalis (Latreille 1802) and P. obscuricornis (Emery 1890), morphological evidence indicates the existence of three broadly sympatric species. Examination of type specimens reveals that the name obscuricornis has been extensively misapplied in the literature, and that the valid name for the widespread species commonly misdiagnosed as P. obscuricornis is P. verenae (Forel 1922). True P. obscuricornis is shown to be an uncommonly collected South American species. The name apicalis is valid as currently employed for that species. A taxonomic key is provided, along with diagnoses, illustrations, and distributional data for all three species.