Data Structures and Algorithms
with Object-Oriented Design Patterns in C++ 
Since each of the elements of 
is either a zero or a one,
there are 
possible values for X.
A brute-force algorithm to solve this problem
finds the best solution by enumerating all the possible values of X.
For each possible value of X we check first
if the constraint 
is satisfied.
A value which satisfies the constraint is called
a feasible solution .
The solution to the problem is the feasible solution which
minimizes 
which is called the
objective function .
Since there are possible values of X
the running time of a brute-force solution is 
.
The running time needed to determine whether a possible value is
a feasible solution is O(n)
and the time required to evaluate the objective function is also O(n).
Therefore, the running time of the brute-force algorithm is 
.
Copyright © 1997 by Bruno R. Preiss, P.Eng. All rights reserved.