Models and methods for forming service packages for solving of the problem of designing services in information systems of providers
DOI:
https://doi.org/10.20535/2786-8729.5.2024.316432Keywords:
service design, service package; service architecture; genetic algorithm; value of serviceAbstract
Today, in the telecommunications industry, service is one of the fundamental concepts. Building a service architecture is a key stage in the service life cycle. Information systems of telecommunications providers are designed, implemented and supported by IT companies based on the End-to-End model. This requires the IT company to solve a number of complex problems. In these conditions, building a service architecture, implementing and providing a service are divided into subproblems. Solutions to subproblems must be integrated to determine the coordinated activities of both the IT company and the provider. In this case, it is necessary to take into account the goals of IT companies, providers and their customers in such a way that it is beneficial to all parties. One of such subproblems is the formation of service packages that the IT company offers to providers. The article proposes formal models for the subproblem of forming service packages that allow taking into account the interests of the IT company and providers. These are multi-criteria nonlinear mathematical programming models. To solve the subproblem of forming service packages, a two-stage algorithm and a modified version of the guided genetic algorithm are proposed. The use of these methods allows us to take into account the interests of the IT company and providers. Also, such important factors that affect the formation of packages as the base price of the service, service dependency, discount system, resource and other constraints of the IT company and providers are taken into account.
The two-stage algorithm at the first stage uses classical algorithms for solving the knapsack problem, and at the second stage implements a compromise scheme to improve the solution. The second of the proposed methods uses three types of tools in combination. The first tool controls the convergence of the genetic algorithm. The second tool determines the choice of the best solutions taking into account the features of the multi-criteria problem. The third tool allows to obtain the best solutions to the optimization problem with the simultaneous choice of a discount strategy. Experimental studies have confirmed the effectiveness of the proposed methods. Their ability to form the basis of the technology of forming service packages as a component of the platform for supporting the life cycle of services is also confirmed.
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