Do ants paint trucks better than chickens? Markets versus response thresholds for distributed dynamic scheduling

Abstract

We studied the dynamic allocation of trucks to paint booths, contrasting two previously proposed schemes in which booths bid against each other for trucks: one based on markets and the other ant-inspired response thresholds. We explore parameter space for several system performance metrics and find that this system is surprisingly easy to optimize and that a number of parameters can be eliminated. We investigate two different threshold reinforcement schemes that give rise to booth specialization and also examine variations of the breaking tie rules that decide among booths when two or more place identical, highest bids for a particular truck. We find that the threshold reinforcement scheme usually used in response threshold applications (local update) fares worse than one with global update of thresholds, and that breaking tie rules previously proposed can be simplified without loss of system performance.