European Journal of Computer Science and Information Technology (EJCSIT)

EA Journals

Genetic Algorithm

Optimizing the Carpool Service Problem with Genetic Algorithm (Published)

Now a day’s traffic congestion is a main issue all over the world so we are proposing a carpool system that will increase the no of occupation seats by decreasing the no of empty seats. This system divided into basically two modules. These modules are the mobile client module and Global Carpool Services module. User first have to submit carpool request using any android based Smartphone and obtain a matches within the mobile client module via the global cloud module. With the help of genetic based carpool algorithm global service module generate acceptable matches.To reduce the time required   and to find a best match we proposed a genetic algorithm for large no of users. Related to the quality of matches and processing time. The experimental results shows that the current root matching algorithm successfully showing the results which are optimal and also operate with the less computational time.

Keywords: Carpool Service, Genetic Algorithm, Optimizing

Metric Genetic-Fuzzy Based Customer Relationship Management Health Model (Published)

Customer Relationship Management (CRM) is a model for managing a company’s interactions with current and future customers. Most of the implemented CRM approaches are subjective in nature, in addition to the serious need to separate feelings of satisfaction or dissatisfaction with the services delivery. Metric Genetic-Fuzzy Based Customer Relationship Management Health Model (MGFBCRMHM) was initiated for these reasons. Unified Modeling Language was utilized for modeling the software system, depicting clearly the interaction between various components and the dynamic aspect of the system. The simulation results utilizing Matrix Laboratory (MATLAB) was satisfactory. This paper demonstrates the practical application of metric based soft computing techniques in the health sector in determining patient’s satisfaction.

Keywords: CRM, Fuzzy Logic, Genetic Algorithm

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