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An engineering case shows that the risk and condition based maintenance task optimization technology can be used to optimize maintenance content and maintenance period, to minimize maintenance deficiencies and maintenance surplus, and to prolong the lifespan of equipment.
Jobs without the task optimization (i.e., the displayed frontiers in Fig. 16) used the number of tasks specified in Table 2.
The visibility of new features that become relevant in new contexts of use and task optimization are also possibilities inherent in the concept of tailoring.
In order to allocate maintenance resources reasonably, ascertain the minimum preventive maintenance requirement, ensure the reliability, availability and safety, this paper carries out a research on Risk and Condition Based Maintenance (RCBM) task optimization technology.
In the final article, "Large-scale global optimization through consensus of opinions over complex networks" by Omid Askari-Sichani and Mahdi Jalili, the authors present a model based on consensus of opinions among agents interacting over a complex networked structure for a large-scale task optimization.
In this approach, each motor command is represented as a linear combination of prefixed basis patterns, and the command for a given task is designed by minimizing a two-termed criterion consisting of a task optimization term and a parameter preference (i.e., sparseness) term.
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Since the task of optimization should be accomplished in between two sampling periods the use of a fast optimization algorithm becomes essential.
The GUI comprises a user input section, a task allocation optimization section, and a control and communication section.
The basic idea of the diversification strategy is to have different probability parameters for slave ants to solve the task scheduling optimization problem.
Finally, our proposed task adjustment optimization enhances the performance of the Pareto-based scheduler by minimizing further the workload's makespan.
In this work, we extend significantly this contribution proposing a global offloading strategy which combines offloading decision and task scheduling optimization.
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