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computes the difference in seconds between two time_t values time: returns the current time of the system as a time_t value, number of seconds, (which is usually time since an epoch, typically the Unix epoch). The value of the epoch is operating system dependent; 1900 and 1970 are often used. See RFC 868. clock
The artificial landscapes presented herein for single-objective optimization problems are taken from Bäck, [1] Haupt et al. [2] and from Rody Oldenhuis software. [3] Given the number of problems (55 in total), just a few are presented here. The test functions used to evaluate the algorithms for MOP were taken from Deb, [4] Binh et al. [5] and ...
For example, in the factoring problem, the instances are the integers n, and solutions are prime numbers p that are the nontrivial prime factors of n. An example of a computational problem without a solution is the Halting problem. Computational problems are one of the main objects of study in theoretical computer science.
Set covering is equivalent to the hitting set problem. That is seen by observing that an instance of set covering can be viewed as an arbitrary bipartite graph , with the universe represented by vertices on the left, the sets represented by vertices on the right, and edges representing the membership of elements to sets.
In his paper Sudoku as a Constraint Problem, [14] Helmut Simonis describes many reasoning algorithms based on constraints which can be applied to model and solve problems. Some constraint solvers include a method to model and solve Sudokus, and a program may require fewer than 100 lines of code to solve a simple Sudoku.
When a program wants to time its own operation, it can use a function like the POSIX clock() function, which returns the CPU time used by the program. POSIX allows this clock to start at an arbitrary value, so to measure elapsed time, a program calls clock(), does some work, then calls clock() again. [1] The difference is the time needed to do ...
A problem is NP-complete if, roughly speaking, it is in NP and is not easier than any other NP problem. Many combinatorial problems, such as the Knapsack problem, the travelling salesman problem, and the Boolean satisfiability problem are NP-complete. For all these problems, the best known algorithm has exponential complexity.
An example is a computer program that processes files. A part of that program may scan the directory of the disk and create a list of files internally in memory. After that, another part of the program passes each file to a separate thread for processing. The part that scans the directory and creates the file list cannot be sped up on a ...