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Applications in phase transition and pattern formation problems confirm the efficiency of the proposed methods.
Besides, a novel coordinates transformation is proposed to represent the relative reduced attitudes in S2, which is shown to be an efficient approach to reduced attitude formation problems.
Both algorithms have been applied to the same set of cell formation problems with alternate routings from literature and representative results are shown.
Investigations have shown that dry machining of titanium workpiece layers leads to increased tool wear, chip formation problems, and surface damage in the aluminum and CFRP-layers.
This paper presents an application of modified Hopfield neural networks in order to solve cell formation problems: the quantized and fluctuated Hopfield neural networks (QFHN).
Accurate knowledge of hydrate phase equilibrium in the presence of inhibitors is crucial to avoid gas hydrate formation problems and to design/optimize production, transportation and processing facilities.
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We call this the sustainable cell formation problem (SCFP).
We present two approaches to solve the cell formation problem.
The results are illustrated by a robot formation problem.
Furthermore, as an extension of the consensus problem, the formation problem is studied.
The self-reconfiguration problem is modeled as an instance of the graph-based coalition formation problem.
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