Dynamic scheduling of flexible manufacturing system using heuristic approach

The problem of decreasing production costs through an appropriate management of available resources is fundamental in the field of industrial production. The performance of a flexible manufacturing system (FMS), not properly supported by an efficient resource management strategy, may be drastically limited, & the advantages derived from its flexibility in terms of production costs may suffer a sharp reduction. Furthermore, an FMS is composed of a large number of components, thus making the identification of a correct strategy for the management more difficult. In this paper a heuristic based genetic algorithm is proposed for generating optimized production plans in flexible manufacturing systems. The ability of the system to generate alternative plans following part-flow changes & unforeseen situations is particularly stressed (dynamic scheduling). The Key-point objective is the reduction of machine idle time obtained by an optimized evolutionary strategy needed to reach the optimal schedule in complex manufacturing systems.

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