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Abstract
This dissertation presents a comprehensive coding system for classfying and describing production scheduling problems of flexible manufacturing systems ( FMSs) Furthermore, it presents two methods for solving loading problem of random FMSs. The first method uses parallel; Genetic Algorithm ( PPGA ) depending on a new genome structure and the second uses a proposed integer programming ( IP ) model . Also, simulation technique is used to study the effect of varying push, pull, and Inventory Sorting Rules ( ISRs ) of FMS components on the system throughput performance measure. Besides the dissertation presents a method for solving the random FMSs. scheduling problem using a simple Genetic Algorithm ( SGA ) depending on a new genome structure.