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As a variant of the RCPSP, the resource availability cost problem (RACP), which has the aim of minimizing the availability costs of renewable resources in order to complete a project subject to a given deadline, is considered in this paper.
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The progression of such intervention need to be assessed because Khat is still cultivated in Faifa, and strengthening of mechanisms for law enforcement is needed to minimize the availability of Khat in the community.
Under the PBC framework, the goal of the study is to increase the system operational availability while minimizing the logistics footprint through the design for reliability.
The suggested optimization model has two objectives: maximizing the system availability and minimizing the total cost of the system.
In this paper, the RAP in repairable series parallel systems is considered, with two objectives (1) maximizing the system asymptotic availability (2) minimizing the total cost.
The benefits of this focus on predictive maintenance include increased system availability by minimizing the occurrence of service affecting failures through tracking of trends and early mitigation.
Two typical redundancy allocation problem formulations, i.e., minimizing the system cost while satisfying required system availability and maximizing the system availability with a limited budget, are studied.
In biosensing applications, when sample availability is limited, minimizing the total analyte volume consumed is especially important.
By maximizing the achievable rates or minimizing the outage probabilities based on the CSI availability, we obtained the optimal transmit power of the full-duplex relay node.
Whereas, we propose a channel selection mechanism using historical availability prediction and utility-based perception learning, minimizing the possibility of interference and starvation.
The second part relates to minimizing the task mapping cost in order to achieve a balanced energy availability through the network.
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