2,632 research outputs found
Optimizing the performance of an integrated process planning and scheduling problem: an AIS-FLC based approach
The present market scenario demands an integration of process planning and scheduling to stay competitive with others. In the present work, an integrated process planning and scheduling model encapsulating the salient features of outsourcing strategy has been proposed. The paper emphasizes on the role of outsourcing strategy in optimizing the performance of enterprises in rapidly changing environment. In the present work authors have proposed an artificial immune system based AIS-FLC algorithm embedded with the fuzzy logic controller to solve the complex problem prevailing under such scenario, while simultaneously optimizing the performance. The authors have shown the efficacy of the proposed algorithm by comparing the results with other random search methods
Investigating a Hybrid Metaheuristic For Job Shop Rescheduling
Previous research has shown that artificial immune systems can be used to
produce robust schedules in a manufacturing environment. The main goal is to
develop building blocks (antibodies) of partial schedules that can be used to
construct backup solutions (antigens) when disturbances occur during
production. The building blocks are created based upon underpinning ideas from
artificial immune systems and evolved using a genetic algorithm (Phase I). Each
partial schedule (antibody) is assigned a fitness value and the best partial
schedules are selected to be converted into complete schedules (antigens). We
further investigate whether simulated annealing and the great deluge algorithm
can improve the results when hybridised with our artificial immune system
(Phase II). We use ten fixed solutions as our target and measure how well we
cover these specific scenarios
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