Rough set techiques for uncertainty management in automated story generation
ACM-SE 36 Proceedings of the 36th annual Southeast regional conference
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Communications of the ACM - E-services: a cornucopia of digital offerings ushers in the next Net-based evolution
Service components for managing the life-cycle of service compositions
Information Systems - Special issue: The 14th international conference on advanced information systems engineering (CAiSE*02)
A declarative approach to composing web services in dynamic environments
Decision Support Systems
A high performance backoff protocol for fast execution of composite web services
Computers and Industrial Engineering - Special issue: Computational intelligence and information technology applications to industrial engineering selected papers from the 33 rd ICC&IE
Evolutionary computing based mobile robot localization
Engineering Applications of Artificial Intelligence
The design with object (DwO) approach to Web services composition
Computer Standards & Interfaces
Feature selection based on rough sets and particle swarm optimization
Pattern Recognition Letters
Topological approaches to covering rough sets
Information Sciences: an International Journal
Computers and Operations Research
Efficient algorithms for Web services selection with end-to-end QoS constraints
ACM Transactions on the Web (TWEB)
Towards a context-based multi-type policy approach for Web services composition
Data & Knowledge Engineering
A hybrid genetic algorithm for the re-entrant flow-shop scheduling problem
Expert Systems with Applications: An International Journal
Engineering Applications of Artificial Intelligence
A hybrid machine learning approach to network anomaly detection
Information Sciences: an International Journal
Learning fuzzy rules from fuzzy samples based on rough set technique
Information Sciences: an International Journal
Fuzzy-genetic approach to aggregate production-distribution planning in supply chain management
Information Sciences: an International Journal
Efficient execution of composite Web services exchanging intensional data
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
A hybrid real-parameter genetic algorithm for function optimization
Advanced Engineering Informatics
Through Personalized Web Service Composition Specification: From BPEL to C-BPEL
Electronic Notes in Theoretical Computer Science (ENTCS)
On acquiring classification knowledge from noisy data based on rough set
Expert Systems with Applications: An International Journal
A GAs based approach for mining breast cancer pattern
Expert Systems with Applications: An International Journal
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
Genetic regulatory network-based symbiotic evolution
Expert Systems with Applications: An International Journal
Towards a community-based, social network-driven framework for Web services management
Future Generation Computer Systems
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Evolutionary computing (EC) techniques have been used traditionally used for solving challenging optimization problems. But the increase in data and information has reduced the performance capacity of the GA, but highlighted the cost of finding a solution by GA. In addition, the genetic algorithm employed in previous literature is modeled to solve one problem exactly. The GA needs to be redesigned, at a cost, for it to be applied to another problem. For these two reasons, this paper proposes a method for incorporating the GA and rough set theory. The superiority of the proposed GA in this paper lies in its ability to model problems and explore solutions generically. The advantages of the proposed solution approach include: (i) solving problems that can be decomposed into functional requirements, and (ii) improving the performance of the GA by reducing the domain range of the initial population and constrained crossover using rough set theory. The solution approach is exemplified by solving the problem of web services composition, where currently the general analysis and selection of services can be excessively complex and un-systemic. Based on our experimental results, this approach has shown great promise and operates effectively.