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In order to prepare for your exams without distractions from lectures etc., the university gives you a few study days, including today. So much for the “no distractions” part ...
Given that study time is rather limited, it is crucial to divide it up well for studying for various exams. In the end, you just want to maximize your GPA, so maybe it’s worth to put up with a C in one course (where a better grade would require a lot of studying) to secure A’s (which can be achieved with relatively little studying each) in all other courses. Clearly, this is a crucial optimization problem, and solving it well will probably benefit you tremendously.
The first line contains a number K ≥ 1, which is the number of input data sets in the file. This is followed by K data sets of the following form:
The first line of a data set contains two numbers n,H, the number of courses you are taking (an integer n between 1 and 10) and the number of hours available for studying (an integer H ≤ 100).
This is followed by n lines, each containing 10 integers. These integers in line i will describe, in the order given, the number of hours you need to study in order to get an A (4.0), A- (3.7), B+ (3.3), B (3.0), B- (2.7), C+ (2.3), C (2.0), C- (1.7), D+ (1.3), D (1.0) in the ith of your courses. The numbers will be non-increasing. The interpretation is that if you study at least that many hours in the particular subject, you will get the given grade. If you don’t even study enough for a D, your grade will be F (0.0).
For each data set, first output “Data Set x:” on a line by itself, where x is its number. Then, output the maximum possible GPA (rounded to two decimals) you can obtain by dividing your H hours of studying between the subjects.
1 3 60 40 37 35 33 30 26 20 10 5 1 10 10 10 10 10 10 10 10 10 1 24 23 22 21 20 20 20 20 20 20
Data Set 1: 3.43