A SOA Approach from Medical Services Optimization using Evolutionary Algorithms

Florin-Claudiu Pop, Marcel Cremene, Mircea-Florin Vaida, and Andrea Şerbănescu


services, composition, QoS, optimization, socioeconomic


Patients rely on the physician for recommending an adequate treatment path for their medical condition. Since there are several possible paths to choose from, the optimal solution should be selected. This paper proposes a method to optimize medical services as business workflows. Such a workflow consists in a set of medical services. Each medical service has different attributes such as: average wait time, rating, distance and cost. For each service type several alternatives of concrete medical services exists. Determining the optimal combination of medical services for a business workflow is an NP-hard problem. Genetic Algorithms (GA) and Differential Evolution (DE) are used to find the optimal solution. The results indicate that DE approach converges faster.

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