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In real-world scenarios, massive demands mi ght be simultaneously raised by massive customers. Mass customization (MC) of services is a cost-effective approach to deal with this scenario by offering a cus tomizabl e composite service that satisfies as many personalized requirements as possible. In this paper, Service Network (SN) is employed to repres ent a customizable composite service, so that MC of services is transformed into a Service Network Planning (SNP) problem. A heuristic algorithm called Iterative Enhancement based Algorithm (IEA) is proposed for SNP. Massive requirements are sorted i n terms of their potential benefit in the descending order, and for each requirement to be dealt with, the algori thm i teratively enhances the preceding constructed SN by the least cos t instead of constructing a new one, so that the final constructed SN keeps the minimal size and complexity and reaches cost-effectiveness. For comparison, two traditional service composition bas ed algorithms called Solution Consolidation based Algorithm (SCA) and Requirement Grouping based Al gorithm (RGA) are presented. Experiments are conducted to prove the superiority of the IEA, and factors that impact the performance of IEA are exploited elaborately.

COST-EFFECTIVE SERVICE NETWORK PLANNING FOR MASS CUSTOMIZATION OF SERVICES