Modelling of an Agent Based-Job Shop Scheduling of Make Span Minimization in a Rigid Machine Setup

Abstract

This paper presents an agent-based model for scheduling job in a

rigid machine setup. The model involved three sequential machines

through which every job must pass followed by one out of three

finishing machines used one per finishing type. For the type of

product that is produced, the raw material must pass through the

first three machines only in one order. Thus, the model developed

took this sequential order into consideration. A well-crafted

scheduler agent that carries out bunching of sorted jobs either in 1

or 2- or 3-days’ bunch(es) per finishing type and selects the best

out of the three approaches. This scheduling technique allows a

certain product type to be scheduled for 1 or 2 or 3 days before

changing to another product type. The result of ten different

monthly orders scheduled with bunching factor 2 had earliest

release dates for eight out of the ten different orders and bunching

factor 3 had earliest release dates for two orders while bunching

factor 1 had none. The agent-based job shop scheduling model was

validated with D.G. Kendall, classical method for poisson arbitrary

distribution with nonpreemptive discipline where the agent-based

model (ABM) compared favorably with the classical model. The

comparative result shows that the modelled agent-based job shop

scheduling had 2.4% improvement to the existing classical model

and should be applied in an industrial set up for makespan

minimization in a rigid machine setup.