Document Type


Date of Award

Spring 5-31-1991

Degree Name

Master of Science in Electrical Engineering - (M.S.)


Electrical and Computer Engineering

First Advisor

Edwin Hou

Second Advisor

Anthony D. Robbi

Third Advisor

Nirwan Ansari


A Flexible Manufacturing System (FMS) consisting of p automated guided vehicles (AGV's), m workstations and n tasks is studied. The main problem investigated in this thesis is to find an optimal or suboptimal task scheduling for p AGV's among m workstations to complete n tasks.

An efficient approach based on genetic algorithms has been designed and implemented to solve the problem of task scheduling for a FMS. Near-optimal, or even optimal, task scheduling is accomplished by genetic algorithms. Simulation results on the algorithm are also discussed.