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The provided information are integrated in a stochastic optimization algorithm to select the optimal buffer allocation.
This article investigates metamodeling opportunities in buffer allocation and performance modeling in asynchronous assembly systems (AAS).
One of the major design problems in the context of manufacturing systems is the well-known Buffer Allocation Problem (BAP).
This design goal is achieved by the observation that bandwidth distribution is equivalent to buffer allocation under FIFO queueing.
Therefore, the purpose of this paper is to present an effective design methodology for buffer allocation in the production system.
In this paper, the description and results of simulation experiments investigating buffer allocation in closed serial production lines are presented.
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Two methods of buffer space allocation at the switches, and two congestion control mechanisms are modeled.
Therefore, we need to determine an optimal recovery policy and buffer time allocation to the ship route in order to minimize the total costs associated with delays and recovery actions, such as increasing sailing speed.
In addition, we study the performance of G-ER under group dynamics and find that the impact of group dynamics can be reduced by some proper buffer resource allocation in one group.
Ongoing work includes optimizing the performance of NNIDS, developing strategies for sustainable operation of the NNIDS under attacks through adaptation and active countermeasures, studying algorithms for distributed and collaborative intrusion detection, and further developing the analytical models for buffer and processor allocation.
Also, buffer-aware resource allocation methods similar to [18] can be employed to efficiently serve the system queues.
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