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The importance of the Markov chain parameters a and b has been shown in previous sections.
By suitably setting the Markov chain parameters, several environment can be modeled.
This research explores the effect of important supply chain parameters on the cost savings realized from collaborative initiatives.
Yao et al. (2007) developed an analytical model that explores how important supply chain parameters affect the cost savings to be realized from collaborative initiatives as VMI.
Furthermore, a number of important managerial insights are presented based on sensitivity analysis of interaction effect of capacity constraints with other supply chain parameters.
We use two sequential linear programming problems – plant location and fleet assignment, with the pressure and temperature state of cargo CO2 as the key CCS chain parameters.
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This is simply because the transmission chain parameter cannot be flexibly changed at the transmitter without the knowledge of CSI, which invokes the necessity of the outage analysis.
The analysis framework takes advantage of the use of process-based models endorsing sensitivity analysis of crucial technological, production and supply-chain parameters.
From validation with PROCHECK, the main-chain parameters match those of a crystallographic structure of 2.0 2.5 Å resolution, with a standard deviation of omega angles slightly larger than expected, due probably to CHARMm parametrization.
The key difference between this model and the flow-sheeting approach used by NREL is that, in the NREL model, the majority of supply-chain parameters are fixed to allow different process designs to be investigated; in our model, the mass balance and equipment structure of each process description are fixed to allow the importance of the other supply-chain parameters to be investigated.
Mugsy relies on a number of parameters including minimum MUM length in Nucmer and the LCB chaining parameters.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com