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Task scheduling for flexible manufacturing systems based on genetic algorithms

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2 Author(s)
Hou, E.S.H. ; Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA ; Li, H.-Y.

The authors present a genetic algorithm approach to solving the task scheduling problem in flexible manufacturing systems (FMSs) An FMS is modeled as a collection of m workstations and p automated guided vehicles (AGVs). The FMS completes a task by performing a series of operations through the workstations, and the parts are transported between the workstations by the AGVs. The problem of task scheduling in an FMS can be stated as finding a schedule for the p AGVs among the m workstations such that n tasks can be completed in the shortest time. The genetic algorithm developed uses a reproduction operator and five mutation operators to perform the task scheduling. Computer simulations of the proposed genetic algorithm are also presented

Published in:

Systems, Man, and Cybernetics, 1991. 'Decision Aiding for Complex Systems, Conference Proceedings., 1991 IEEE International Conference on

Date of Conference:

13-16 Oct 1991