497 The calculation of the optimization components is given as follows, disaggregating each subcomponent to the corresponding parameters and decision variables associated. In case of the overall cost, it is composed of truck-related, shovel-related, and processing-related costs. ij.$$ AG1G/kG !",6 =hUAB!",6,& &∈; ∗8AY ∀$'∈fℂ,]∈ℙ (2) l.$%$!",6 =hU>>ql!",6,<Y <∈= +hU>rql!",6,!Y !∈9 +hU8Aq:!",6,& ∗8l6,&Y &∈; ∀$'∈fℂ,]∈ℙ (3) 8G/#"%&G$!",6 =hU:8,!",6,& ∗]]k6,& +:8c!",6,& ∗]]"6,&Y &∈; + hU:i,!",6,& ∗]sk6,& +:ic!",6,& &∈; ∗]s"6,&Y ∀$'∈fℂ,]∈ℙ (4) Gross revenue function for each period is given by Equation 2, where VXED,&,, represents the recovered metal and LV is the price evaluated for the product at the moment of sale. In Equation 3, the operational costs are computed based on SSΩsED,&,> (trucks’ operating costs), SJΩsED,&,E (shovels’ operating cost), LVΩOED,&,, (tonnage delivered for processing) and Ls&,, (processing cost). In the case of total penalties, Equation 4 displays the disaggregation of penalties from production variations (OLáED,&,, as material surplus, OL:ED,&,, as material slack, 11Ç&,, and 11Ñ&,, for the cost of variation above and below the production target, respectively) and penalties from grade variations (OäáED,&,, as difference of grade over target, Oä:ED,&,, for grade under target, 1æÇ&,, and 1æÑ&,, for the cost of grade variation above and below target grade, respectively). The model evaluates ancillary variables to store and simplify the values of mining production (PROD), weighted grade (GRAD), and recovered metal (RM) for each destination and period. These variables are given by: 8Aq:!",6,& =hhhhU7!",6,<,',&,( ∗!l6,< <∈= !∈9 '∈? (∈> ∗<!",6,!,'Y ∀$'∈fℂ,]∈ℙ,E∈t (5) iA0:!",6,& =hhhhu 7!",6,<,',&,( ∗!l6,< ∗<!",6,!,'∗i' 8Aq:!",6,& +ℯ w <∈= !∈9 '∈? (∈> ∀$' ∈fℂ,] ∈ℙ,E ∈t (6)
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