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CVaR is minimized using linear programmes, while a multiobjective genetic algorithm is designed for minimizing VaR, considering two scenarios for each currency.
This is because i) active-set methods are usually the fastest ones for quadratic and linear programmes of small and median size; and ii) expensive computations, like solving systems of linear equations, can be shared in the active-set method.
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In the paper on hand, we give a detailed problem description and model the problem as a binary linear programme.
Process variables are optimized simultaneously with the plant structure by formulating the whole optimization problem as a non linear programme (NLP).
Among others, the optimisation task has been formulated as integer linear programme [5, 6], network flow programme [7 10], quadratic Boolean programme [11], energy minimisation [12, 13], generalised clique graphs [14, 15] and maximum weight-independent set problem [16].
The model takes into account power losses during the allocation of power generated from renewables to appliance loads, and is formulated as a linear programme (LP) based on a superstructure including all possible power allocation options in a typical HPS.
Finally, DEA model is designed and resolved as standard linear programme.
They include econometric [ 41, 42] to linear programme models [ 38, 40, 43] and alternatives such as systems dynamics and stochastic models which take account of uncertainty [ 30, 44].
The resulting optimization problem to be solved is a mixed integer non-linear programme (MINLP).
The proposed site layout problem with multiple construction stages is formulated as a binary-mixed-integer-linear programme, which can be solved by a standard branch-and-bound algorithm using the commercial software package LINGO.
For ZEN14Glc and ZEN16Glc, a short isocratic elution phase between 7 and 9 min had to be introduced during the linear gradient programme to achieve chromatographic separation.
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