
Explanation of Solution
Formulation of a Linear
Let “x1” be the number of dollars invested in stocks.
The “x2” be the number of dollars invested in loans.
As every dollar invested in stocks gives 10 cents profits, so the total profit on stocks would be $0.1x1. Likewise, the total profit on loan would be $0.15x2.
Since the objective is to maximize total profit earned from Erica’s investment, the objective function is defined as follows:
Constraint 1:
At least, 30% of total invested money must be invested in stocks. The “x1+ x2” is the total money invested in the investment. Since the number of dollars invested in stocks must be at least 30% of the total investment, the constraint is defined as follows:
Constraint 2:
At least, $400 of all money must be invested in loans, so the constraint is defined as:
Constraint 3:
At most, $1000 is invested in stocks and loans, so the constraint is defined as:
Therefore, the formulation to the given linear program is:

Want to see the full answer?
Check out a sample textbook solution
Chapter 3 Solutions
Introduction to mathematical programming
- Could you help me to know features of the following concepts: - commercial CA - memory integrity - WMI filterarrow_forwardBriefly describe the issues involved in using ATM technology in Local Area Networksarrow_forwardFor this question you will perform two levels of quicksort on an array containing these numbers: 59 41 61 73 43 57 50 13 96 88 42 77 27 95 32 89 In the first blank, enter the array contents after the top level partition. In the second blank, enter the array contents after one more partition of the left-hand subarray resulting from the first partition. In the third blank, enter the array contents after one more partition of the right-hand subarray resulting from the first partition. Print the numbers with a single space between them. Use the algorithm we covered in class, in which the first element of the subarray is the partition value. Question 1 options: Blank # 1 Blank # 2 Blank # 3arrow_forward
- 1. Transform the E-R diagram into a set of relations. Country_of Agent ID Agent H Holds Is_Reponsible_for Consignment Number $ Value May Contain Consignment Transports Container Destination Ф R Goes Off Container Number Size Vessel Voyage Registry Vessel ID Voyage_ID Tonnagearrow_forwardI want to solve 13.2 using matlab please helparrow_forwarda) Show a possible trace of the OSPF algorithm for computing the routing table in Router 2 forthis network.b) Show the messages used by RIP to compute routing tables.arrow_forward
- using r language to answer question 4 Question 4: Obtain a 95% standard normal bootstrap confidence interval, a 95% basic bootstrap confidence interval, and a percentile confidence interval for the ρb12 in Question 3.arrow_forwardusing r language to answer question 4. Question 4: Obtain a 95% standard normal bootstrap confidence interval, a 95% basic bootstrap confidence interval, and a percentile confidence interval for the ρb12 in Question 3.arrow_forwardusing r languagearrow_forward
- using r languagearrow_forwardusing r language Obtain a bootstrap t confidence interval estimate for the correlation statistic in Example 8.2 (law data in bootstrap).arrow_forwardusing r language Compute a jackknife estimate of the bias and the standard error of the correlation statistic in Example 8.2.arrow_forward
- Operations Research : Applications and AlgorithmsComputer ScienceISBN:9780534380588Author:Wayne L. WinstonPublisher:Brooks Cole
