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A B S T R A C T This paper addresses the scheduling of machines, an Automated Guided Vehicle (AGV) and two robots in a Flexible Manufacturing System (FMS) formed in three loop layouts, with objectives to minimize the makespan, mean flow time and mean tardiness. The scheduling optimization is carried out using Sheep Flock Heredity Algorithm (SFHA) and Artificial Immune System (AIS) algorithm. AGV is used for carrying jobs between the Load/Unload station and the machines. The robots are used for loading and unloading the jobs in the machines, and also used for transferring jobs between the machines. The algorithms are applied for test problems taken from the literature and the results obtained using the two algorithms are compared. The results indicate that SFHA performs better than AIS for this problem.

A new evolutionary computation algorithm, Superbug algorithm, which simulates evolution of bacteria in a culture, is proposed. The algorithm is developed for solving large scale optimization problems such as scheduling, transportation and assignment problems. In this work, the algorithm optimizes machine schedules in a Flexible Manufacturing System (FMS) by minimizing makespan. The FMS comprises of four machines and two identical Automated Guided Vehicles (AGVs). AGVs are used for carrying jobs between the Load/Unload (L/U) station and the machines. Experimental results indicate the efficiency of the proposed algorithm in its optimization performance in scheduling is noticeably superior to other evolutionary algorithms when compared to the best results reported in the literature for FMS Scheduling.