Dynamic and adaptive grouping maintenance strategies: New scalable optimization algorithms

This paper focuses on new efficient and adaptive optimization algorithms to cope with the maintenance grouping problem for series, parallel, and complex systems. We propose a Particle Swarm Optimization approach to cope with small and medium problem sizes, and that will be used to benchmark existing heuristic solutions such as Genetic Algorithms. To address scalability and adaptability issues, we propose a new dynamic optimization algorithm based on a clustering technique. This clustering-based solution is formulated using an Integer Linear Programing approach to guarantee the convergence to global optimal solutions of the considered problem. We show the performance of the proposed approaches with a clear advantage to the clustering-based algorithm that we recommend for large industrial systems.

A steady-state grouping genetic algorithm for the rainbow spanning tree problem

Given a connected, undirected and edge-colored graph, the rainbow spanning tree (RSF) problem aims to find a rainbow spanning forest with the minimum number of rainbow trees, where a rainbow tree is a connected acyclic subgraph of the graph whose each edge is associated with a different color. This problem is $NP$-Hard and finds several applications in distinguishing among various types of connections. Being a grouping problem, this paper proposes a steady-state grouping genetic algorithm (SSGGA) for the RSF problem. To the best of our knowledge, this is the first work on steady-state grouping genetic algorithm for this problem. While keeping in view of grouping aspects of the problem, each individual, in the proposed SSGGA, is encoded as a group of rainbow trees, and accordingly a problem-specific crossover operator is designed. Moreover, SSGGA uses the idea of two steps in its replacement scheme. All such elements of SSGGA coordinate effectively and overall help in finding high quality solutions. Computational results obtained over a set of benchmark instances show that overall SSGGA, in terms of solution quality, is superior to all other existing approaches in the literature for this problem.

State support and regulation of rural green tourism enterprises development

The subject of the research is theoretical, methodical and practical aspects of state support and regulation of rural green tourism enterprises development. The purpose of the work is to substantiate the directions, mechanisms and instruments of state support and regulation of the development of rural green tourism enterprises for the future. The methodological basis of the article was both general scientific and special methods of scientific knowledge. Methods were used: historical, dialectical, system-structural analysis and synthesis, statistical-economic, SWOT-analysis, grouping, problem-targeted approach. Results of work. The article highlights the problems, factors and prospects of state support and regulation of rural green tourism enterprises development. The conditions, resources, mechanisms and instruments of state support and regulation are identified. Reasonable sources of their spread and growth. Forms of monitoring, reporting and accounting are proposed. Functions have been defined to improve state support, regulation and management of rural green tourism enterprises development in the future. The field of application of results. The materials, results and conclusions of the article can be used in the activities of rural territorial communities, local self-government bodies, enterprises and agro-villages, higher education institutions of relevant specialization and faculties of economics and management. Conclusions. Rural green tourism is a relatively new type of rural activity. It is useful for both holidaymakers and owners – rural residents, entrepreneurs, rural communities, regions and the state as a whole. Its businesses and agro-settlements contribute to the development of many related businesses in other industries; preservation of national spirituality, popularization of Ukrainian culture; dissemination of knowledge and information about the historical, natural, ethnographic features of the country. It deserves all the support from the state, public organizations, large agribusiness, rural territorial communities.

A Performance Analysis of Detecting Credit Card Fraud by using CT18 Method

Credit cards are a significant component of everyday life. Whether purchasing gas and supermarket stores or reserving a hotel and lease a car for the next holiday. Credit cards are a pleasant and safe type of client payment. Advantages that differ from harm security on payments to the convenience of disputing suspect fees or suspicious activity make credit cards such an appealing form of transaction. It takes an hour for any time activities, online shopping, and paperless system. As the amount of credit card customers rises day by day, significant illegal activities eventually enhance. CT18 technique is the procedure for categorizing information directed at reformatting observations into CT18, whereby each observation belongs to the closest mean cluster. This is one of the simplest unsupervised learning algorithms that solve the well-known grouping problem