Sentence examples for representation of supply from inspiring English sources

Representation of supply chains at a level sufficient to capture the essential system interactions requires a high-level architecture that combines simulation (SIM) and optimization (OPT) techniques.

The main objective of this approach is to overcome the computational complexity associated with solving the underlying large-scale mixed integer linear problem and to provide a better representation of supply chain reality.

Our approach provides for excellent representation of supply-chain operations, allows for very detailed operational data to be gathered, and provides efficient representation of concurrent supply-chain activities in a manner that avoids preemption.

With objective costs as thermal comfort (deviation of room temperature from required temperature) and energy measure (Ecm) explicit MPC design for this building model is executed based on its state space representation of the supply water temperature (input)/room temperature (output) dynamics.

The hybrid analytical and simulation approach in this study is used for giving a more realistic representation of the supply chain network.

Therefore, a more detailed representation of complex supply chains is achieved, allowing the solution of larger optimization problems in acceptable time.

The model is based on a complex, data-rich representation of global supply and demand of biomass in the year 2000.

This architecture allows for a natural, realistic representation of different supply-chain constructs and subsystems while following a consistent overall viewpoint.

We present a conceptual architecture that combines simulation formalisms, allowing an agent representation of the supply-chain infrastructure while enabling a process-oriented approach to representing orders.

We use the Medical Subject Headings (MeSH) of MEDLINE/PubMed to identify publications within the categories "Diseases" (C), "Drugs and Chemicals" (D), "Analytic, Diagnostic, and Therapeutic Techniques and Equipment" (E) and use these as knowledge representations of demand, supply, and technological capabilities, respectively.

These GIS systems are, therefore, particularly well adapted to the representation of drinking water supply systems (Blindu 2004).