Above are papers related to the following paper: [Paper_ID] Paper #4983. 	[Title] A Computational Environment for Exhaust Nozzle Design [Abstract] The Nozzle Design Associate (NDA) is a computational environment for the design of jet engine exhaust nozzles for supersonic aircraft. NDA may be used either to design new aircraft or to design new nozzles that adapt existing aircraft so they may be reutilized for new missions. NDA was developed in a collaboration between computer scientists at Rut-gers University and exhaust nozzle designers at General Electric Aircraft Engines and General Electric Corporate Research and Development. The NDA project has two principal goals: to provide a useful engineering tool for exhaust nozzle design, and to explore fundamental research issues that arise in the application of automated design optimization methods to realistic engineering problems. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #7867. 	[Title] Knowledge-Based Re-engineering of Legacy Programs for Robustness in Automated Design [Abstract] Systems for automated design optimization of complex real-world objects can, in principle, be constructed by combining domain-independent numerical routines with existing domain-specific analysis and simulation programs. Unfortunately, such legacy analysis codes are frequently unsuitable for use in automated design. They may crash for large classes of input, be numerically unstable or locally non-smooth, or be highly sensitive to control parameters. To be useful, analysis programs must be modified to reduce or eliminate only the undesired behaviors, without altering the desired computation. To do this by direct modification of the programs is labor-intensive, and necessitates costly revalidation. We have implemented a high-level language and run-time environment that allow failure-handling strategies to be incorporated into existing Fortran and C analysis programs while preserving their computational integrity. Our approach relies on globally managing the execution of these programs at the level of discretely callable functions so that the computation is only affected when problems are detected. Problem handling procedures are constructed from a knowledge base of generic problem management strategies. We show that our approach is effective in improving analysis program robustness and design optimization performance in the domain of conceptual design of jet engine nozzles. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #315789. 	[Title] A Transformation System for Interactive Reformulation of Design Optimization Strategies [Abstract] Automatic design optimization is highly sensitive to problem formulation. The choice of objective function, constraints and design parameters can dramatically impact the computational cost of optimization and the quality of the resulting design. The best formulation varies from one application to another. A design engineer will usually not know the best formulation in advance. In order to address this problem, we have developed a system that supports interactive formulation, testing and reformulation of design optimization strategies. Our system includes an executable, data-flow language for representing optimization strategies. The language allows an engineer to define multiple stages of optimization, each using different approximations of the objective and constraints or different abstractions of the design space. We have also developed a set of transformations that reformulate strategies represented in our language. The transformations can approximate objective and constraint functions, abstract or re-parameterize a search space, or divide an optimization into multiple stages. The system is applicable to design problems in which the artifact is governed by algebraic and ordinary differential equations. We have tested the system on problems of racing yacht and jet engine nozzle design. We report experimental results demonstrating that our reformulation techniques can significantly improve the performance of automatic design optimization. Our research demonstrates the viability of a reformulation methodology that combines symbolic program transformation with numerical experimentation. It is an important first step in a research programme aimed at automating the entire strategy formulation process. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #1138027. 	[Title] Problem Formulation, Program Synthesis and Program Transformation Techniques for Simulation, Optimization and Constraint Satisfaction (Research Statement) [Abstract]  Please summarise all the given information.

Paper #4983 has the title `A Computational Environment for Exhaust Nozzle Design  
` and the abstract `The Nozzle Design Associate (NDA) is a computational environment for the design of jet engine exhaust nozzles for supersonic aircraft. NDA may be used either to design new aircraft or to design new nozzles that adapt existing aircraft so they may be reutilized for new missions. NDA was developed in a collaboration between computer scientists at Rut-gers University and exhaust nozzle designers at General Electric Aircraft Engines and General Electric Corporate Research and Development. The NDA project has two principal goals: to provide a useful engineering tool for exhaust nozzle design, and to explore fundamental research issues that arise in the application of automated design optimization methods to realistic engineering problems. 
`.
Question: Which category should Paper #4983 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #4983 has the title `A Computational Environment for Exhaust Nozzle Design  
` and the abstract `The Nozzle Design Associate (NDA) is a computational environment for the design of jet engine exhaust nozzles for supersonic aircraft. NDA may be used either to design new aircraft or to design new nozzles that adapt existing aircraft so they may be reutilized for new missions. NDA was developed in a collaboration between computer scientists at Rut-gers University and exhaust nozzle designers at General Electric Aircraft Engines and General Electric Corporate Research and Development. The NDA project has two principal goals: to provide a useful engineering tool for exhaust nozzle design, and to explore fundamental research issues that arise in the application of automated design optimization methods to realistic engineering problems. 
`.
Question: Which category should Paper #4983 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].

This paper should be classified into: Genetic_Algorithms