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Capabilities of enhanced simulated-annealing-based algorithms in solving process planning problems in reconfigurable manufacturing are investigated.
This paper presents these new cubatures (based on orthogonal arrays) from a practitioner's point of view and illustrates their remarkable efficiency in solving process systems engineering problems, namely those under the classes of simulation under uncertainty, variance-based global sensitivity analysis and optimization under uncertainty.
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In the solving process, conceptual variations can occur through which scientific knowledge (theories, methods and languages) evolves.
The optimization mechanism of threshold algorithms is investigated in the solving process of a random Euclidean traveling salesman problem.
Combining the Probability Neural Network (PNN) and Orthogonal Experimental Design (OED), an Enhanced Probability Neural Network (EPNN) is proposed in the solving process.
Some convergence results are given, and an effective technique for choosing a reasonable initial solution is designed in the solving process; an example is given to elucidate it.
In the solving process, the typical hierarchy structure usually has three levels: (1) alternative, (2) criteria, and (3) objective, as presented in Fig. 1.
Traditional direct methods for power flow calculation require forward-backward sweeping in the solving process and it is difficult to realize this as a vectorized or parallel calculation.
ensures people stay engaged in the problem solving process.
This is why the approach to selling the solution must be grounded in the problem solving process.
Similar to STEM, collaboration is typically embedded in the problem solving process and critical to honing negotiation skills to arrive at potential solutions (Land 2013).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com