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The strategy s ∗ generated by the algorithm solves program (2 - 6).
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Furthermore, the memory requirements needed by the algorithm when solving those instances may be so high that the available memory may not be enough.
with c, d > 0 and where, again, c represents the time taken by the algorithm to solve the base case.
Thus, there are many scholars and researchers who have discussed stability of the iterative sequence generated by the algorithm for solving the investigated problems.
In computer science, the complexity analysis of an algorithm is based on determining mathematically the quantity of resources needed by the algorithm to solve the problem for which it has been designed.
So the time taken by the algorithm to solve the problem for which it has been designed is denoted by (T^{A}(n)), where (nin mathbb{N}) represents the size of the input data to be processed.
Of course, and similarly to the O -notation case, when the time taken by the algorithm to solve the problem f is unknown, the function g yields an 'approximate' information of the running time of the algorithm in the sense that the algorithm takes a time to solve the problem bounded below by g.
This is usually done by means of the asymptotic analysis in which the running time of an algorithm is denoted by a function T : N → ( 0, ∞ ] in such a way that T ( n ) represents the time taken by the algorithm to solve the problem under consideration when the input of the algorithm is of size n.
In order tocompare the complexity of all algorithms solving the same problem, the running time ofcomputing of each algorithm is denoted by a function T : N → ( 0, ∞ ] in such a way that T ( n ) represents the time taken by the algorithm to solve theproblem under consideration when the input of the algorithm is of size n.
Our implementation was inspired by the algorithm applied to solve traveling salesman problems.
By implementing the algorithm to solve 75 benchmark test problems available in the literature, the obtained results indicate that the algorithm developed in this paper outperforms the existent similar state-of-the-art algorithms.
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