Linear Programming in Applied Mathematics and Computer Science

Algorithms are special formulas, or applications of a particular theorem, that might be converted for different variables. Considering the algorithmic rationale, the same path can lead various times, under different circumstances, to a common goal. These principles in mathematics have been esteemed in computer science in order to provide software applications oriented toward to fast and efficient data conversion. By data conversion, we mean any information that can be efficaciously processed in order to reach a pre-established goal. So, the major change occurred the moment when theorems in mathematics were successfully translated into advanced application, using friendly and easy to use interfaces. Actually, any software application, having been implemented to perform a certain rationale-based task, is an advanced representation of a pattern used in mathematics or in economy.For instance, linear programming algorithms have been successfully converted into extensive application providing profitability solutions for various demands. To put it differently, algorithms are explored as cutting-edge solutions in computer science, for instance linear programming examples have a totally different value in computer science. As a matter of fact, these examples are optimized models, converted into sophisticated platforms and interfaces; A computerized algorithm has the same starting point as a mathematics model, yet, the differences are noticeable when we compare results and efficiency parameters. By means of a linear programming software application, users can reduce a very demanding and meticulous process based upon long calculation.The benefits of linear programming solutions are unquestionable. Yet the implementation a software application relying on linear programming models has assigned to algorithmic method a wider understanding. And by wider availability, we mean the fact that the simplex method or the converted method has been aligned to users who need the final result of the model, and are less interested in the way an automatic system has completed the rationale. The formula, which can show them the way to optimal profit, is the only thing that matters. Furthermore, linear programming solver takes over the most difficult part of the process, making the LP optimization an easy-to-access solution. Along with the easy-access feature, a computer-based solution applying the simplex method or the revised method can be customized for different activity domains. Even though transportation and logistics, engineering, or computer sciences make use of the same algorithm, the functioning principle is somehow adjusted to the specific features of the realm, considering the fact that profit is differently approached by different people.