Can I get some help resolving this problem?

A linear programming computer package is needed. Romans Food Market, located In Saratoga, New York, carries a variety of specialty foods from around the world. Two of the store's leading products use the Romans Food Market name: Romans Regular Coffee and Romans DeCaf Coffee. These coffees are blends of Bnizilian Natunil and Colombian Mild coffee beans, which are purchased from a distributor located In New York City. Because Romans purchases large quantities, the coffee beans may be purchased on an as-needed basis for a price 10% higher than the market price the distributor pays for the beans. The current market price is $0.47 per pound for Brazilian Natural and $0.62 per pound for Colombian Mild. The compositions of each coffee blend are as follows. Blend Bean Rnular Doc-f Brazilian Natural 75% 40% Colombian Mild 25% 60% Romans sells the Regular blend for $3. 60 per pound and the DeCaf blend for $4.40 per pound. Romans would like to place an order for the Bnazllian and Colombian coffee beans that will enable the production of 1,200 pounds of Romans Regular coffee and ?00 pounds of Romans Decaf coffee. The production cost is $0.80 per pound for the Regular blend. Because of the extra steps required to produce DeCaf, the production cost for the Decaf blend Is $1.05 per pound. Packaging costs for both products are $0.25 per pound. Formulate a linear programming model that can be used to determine the pounds of Brazilian Natural and Colombian Mild that will maximize the total contribution to profit. (Let BR - pounds of Brazilian beans purchased to produce Regular, ED - pounds of Bnizllian beans purchased to produce DeCaf, CR - pounds of Colombian beans purchased to produce Regular, and CD - pounds of Colombian beans purchased to produce DeCaf.) Max it. Regular % constraint DeCaf % constraint Pounds of Regular Pounds of DeCaf What is the optimal solution and what is the contribution to prot (in 5)? (Round your contribution to prot to two decimal places.) (BR, so, CR, co) - Profit - S