Abstract.A novel approach for automatic design synthesis and optimization using evolutionary algorithms (EA) is introduced in the paper. The approach applies to component-based systems in general and is demonstrated with a heating, ventilating and air-conditioning (HVAC) systems problem. The whole process of the system design, including the initial stages that usually entail significant human involvement, is treated as a constraint satisfaction problem. The formulation of the optimization process realizes the complex nature of the design problem using different types of variables (real and integer) that represent both the physical and the topological properties of the system; the objective is to design a feasible and efficient system. New evolutionary operators tailored to the component-based, spatially distributed system design problem have been developed. The process of design has been fully automated. Interactive supervision of the optimization process by a human-designer is possible using a specialized GUI. An example of automatic design of HVAC system for two-zone buildings is presented.

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345-348Additional Information:• This is a conference paper [ c IEEE]. It is also available from: http://ieeexplore.ieee.org/ Personal use of this material is permitted.However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ABSTRACT This paper presents a comparative study of three of the emerging frequency domain convolutive blind source separation (FDCBSS) techniques i.e. convolutive blind separation of non-stationary sources due to Parra and Spence, penalty function-based joint diagonalization approach for convolutive blind separation of nonstationary sources due to Wang et al. and a geometrically constrained multimodal approach for convolutive blind source separation due to Sanei et al.Objective evaluation is performed on the basis of signal to interference ratio (SIR), performance index (PI) and solution to the permutation problem. The results confirm that a multimodal approach is necessary to properly mitigate the permutation in BSS and ultimately to solve the cocktail party problem. In other words, it is to make BSS semiblind by exploiting prior geometrical information, and thereby providing the framework to find robust solutions for more challenging source separation with moving speakers.Index Terms-Frequency domain (BSS), geometrical constraints, orthogonal/nonorthogonal constraints, penalty functions, cocktail party problem and multimodal signal separation.

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