A factory produces \( m \) (i = 1, 2, ..., m) products, each of which requires processing on \( n \) (j = 1, 2, ..., n) workstations. Let \( a_{ij} \) be the amount of processing time that one unit of the \( i^{th} \) product requires on the \( j^{th} \) workstation. Let the revenue from selling one unit of the \( i^{th} \) product be \( r_i \) and \( h_i \) be the holding cost per unit per time period for the \( i^{th} \) product. The planning horizon consists of \( T \) (t = 1, 2, ..., T) time periods. The minimum demand that must be satisfied in time period \( t \) is \( d_{it} \), and the capacity of the \( j^{th} \) workstation in time period \( t \) is \( c_{jt} \). Consider the aggregate planning formulation below, with decision variables \( S_{it} \) (amount of product \( i \) sold in time period \( t \)), \( X_{it} \) (amount of product \( i \) manufactured in time period \( t \)) and \( I_{it} \) (amount of product \( i \) held in inventory at the end of time period \( t \)). \[ \text{max} \sum_{t=1}^{T} \sum_{i=1}^{m} (r_i S_{it} - h_i I_{it}) \] subject to \[ S_{it} \ge d_{it} \forall i, t \] <capacity constraint>
<inventory balance constraint>
\[X_{it}, S_{it}, I_{it} \ge 0; \, I_{i0} = 0 \] The capacity constraints and inventory balance constraints for this formulation are
A cement company has three factories which transport cement to four distribution centres. The daily production of each factory, the demand at each distribution centre, and the associated transportation cost per tonne from factory to distribution centre are given in the Table.

Considering the actual demand and the forecast for a product given in the table below, the mean forecast error and the mean absolute deviation, respectively, are:

P and Q play chess frequently against each other. Of these matches, P has won 80% of the matches, drawn 15% of the matches, and lost 5% of the matches.
If they play 3 more matches, what is the probability of P winning exactly 2 of these 3 matches?