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Using Genetic Algorithms to Navigate Partial Enumerable Problem Space for Web Services Composition

机译:使用遗传算法导航Web服务组合的部分令人令人令人令人令人令人令人令人令人令人令人令人令人令人令人令人令人令人令人纪念的问题空间

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Web services have received much interest to support business to business or enterprise application integration but how to combine these services optimally in a continually growing search space is always a challenge. This paper investigates composing business processes from individual services as a planning problem where a planner determines the execution order and other constraints among services in a process. When there are a large number of Web services available, it is not easy to find an execution path of Web services composition that can satisfy the given request, since the search space for such a composition problem is in general exponentially increasing. The planner has to work with a problem space that is not fully enumerable. This paper presents a method that combines Genetic Algorithms (GA) with planning to optimize composition results within an incompletely observed problem space. GA helps to navigate the search in the whole space. At each loop of GA, Web service data are queried and a new subspace is built. The planner works with the subspace and calculates a feasible solution. We test our method on a travel domain. The result is an optimized solution, though global optimization is not guaranteed.
机译:Web服务已收到对企业或企业应用程序集成的支持很多兴趣,但如何在不断增长的搜索空间中最佳地将这些服务结合起来始终是一个挑战。本文调查从个别服务中的业务流程作为计划问题,其中规划员在过程中确定服务中的执行顺序和其他约束。当有大量的Web服务可用时,不容易找到可以满足给定请求的Web服务组合的执行路径,因为这种组成问题的搜索空间一般是指数增加。规划师必须使用不完全令人令人令人愉快的问题空间。本文提出了一种将遗传算法(GA)与规划优化成分在不完全观察到的问题空间内的方法。 GA有助于在整个空间中导航搜索。在每个GA的循环中,查询Web服务数据并构建新子空间。该计划者适用于子空间并计算可行的解决方案。我们在旅行领域测试我们的方法。结果是优化的解决方案,但不保证全局优化。

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