Web services are being adopted, more and more, as a viable means of accessing Web-based applications. At present, there is a trend towards deploying business processes as composite Web services, known as Web services compositions. Web services compositions are synthesized by researchers from elementary Web services, offering the opportunity for service providers and application developers to create value-added services, through Web services composition. However, a problem exists in the current distribution process of Web services compositions: the general analysis and selection of services can be overly complex and un-systemic. Genetic algorithms (GA) has been widely used to solve optimization problems for large scale and complex systems. However, when insufficient knowledge is incorporated, GA is less efficient in terms of searching for an optimal solution. This paper develops a generic genetic algorithm incorporating knowledge extracted from the rough set theory. The advantages of the proposed solution approach include improving the performance of the GA by reducing the domain range of initial population, rule constraining crossover process and rule constrained mutation process, using the rough set theory for composite Web services. Also by proposing the hybrid approach, the GA and rough set theory can operate effectively thus to produce an optimal solution (the best combination of Web services).

At the beginning of the 21st century, the emergence of knowledge management is viewed as a natural evolution. Knowledge management is defined as the formal management of knowledge for facilitating creation, access, and reuse of knowledge, typically by using advanced technology. To be easily communicated and shared, tacit knowledge has to be explicated as explicit knowledge (e.g., in product specification or a scientific formula or production rules); and this explicit knowledge has to be shared as applicable data through the use of information technology. Product design is such a business process that a great part of the design knowledge is often a tacit type, being difficult to share, or available only in forms of natural language documents. However, the expertise recorded in these documents is an essential resource of successful competition in the market. This paper presents a knowledge explication and sharing approach; specifically focusing on the knowledge management of modular product design. The solution approach involves modeling modular products, formulating the explicit knowledge, discovering new design knowledge with data mining, and sharing the knowledge with web services technology. The proposed approach is to be applied to an actual case of motherboard design/assembly in one of the largest PC manufacturing enterprises.