A heuristic for solving the grade of services steiner minimum tree problem

The goal of this research is to devise a heuristic to solve the Grade of Services Steiner Minimum Tree (GOSST) problem. This problem seeks a network with a minimum construction cost that nterconnects all terminal points with additional non-terminal points. The problem can be applied to the design of communication networks offering graduated services. Because the GOSST problem is known to be NP-Complete, a reasonable heuristic is necessary for its practical application, despite some inherent limitations. Most research on GOSST has concentrated on geometric analyses and proposed approximation algorithms. However, since all published solutions for optimization problems require enormous computational power and memory space, they remain impractical. In this research, a feasible heuristic for the GOSST problem is proposed, implemented and analyzed. The proposed heuristic is built by integrating eight GOSST methods. Each method has its own individual merits in terms of certain user requests. Therefore, the proposed heuristic can save network construction costs, while satisfying other user requests such as determining the shortest total network length and the maximum total network capacity. The proposed heuristic reduces the network construction cost by 36.7% compared to the grade of service MST (G-MST), which is used as the experimental control. The proposed heuristic promises to provide a more economic network construction design while satisfying the goal of the GOSST problem and user requests. Additionally, a multiple security grade network system is presented as an example of an application of the proposed GOSST heuristic.