Optimization in business strategy as a part of sustainable economic growth using clique covering of fuzzy graphs

In this paper, new concepts to use clique covering of a fuzzy graph are introduced for optimization of parameters involved in business strategy. For this purpose, four algorithms are designed for finding necessary parameters and sets of a fuzzy graph which is helpful for constructing a cordon of linear programming problems. The linear programming problems are constructed with suitable optimization functions and constraints. The strengths of the cliques present in fuzzy graph get a new look in this paper. Facility location problems are characterized and solved with a new strategy optimization problems by using concept of clique covering of fuzzy graphs for a smooth business strategy to have a maximized total gain. This optimization process will help for developing a part of sustainable economic growth all over the world. Some new definitions are given with relevant examples of fuzzy graphs. An illustration is given to elaborate all mathematical terminologies. Also, a real-life application to optimize different parameters in a business network by solving the programming problems with the help of the mathematical software LINGO keeping the fuzziness of the parameters involved in the considered fuzzy graph.

Automated summary

This paper introduces new concepts involving clique covering of a fuzzy graph for optimizing business strategy parameters. It presents four algorithms for finding necessary parameters and sets of a fuzzy graph to construct a linear programming cordon. By characterizing and solving facility location problems with this approach, the paper aims to maximize total gain and contribute to sustainable economic growth worldwide.