Crossover operators play a very important role by creation of genetic algorithms (GAs) which are applied in various areas of computer science, including combinatorial optimization. In this paper, fifteen genetic crossover procedures are designed and implemented using a modern C# programming language. The computational experiments have been conducted with these operators by solving the famous combinatorial optimization problem-the quadratic assignment problem (QAP). The results of the conducted experiments on the characteristic benchmark instances from the QAP instances library QAPLIB illustrate the relative performance of the examined crossover operations. All crossover procedures are publicly available with the intention that the GA researchers will choose a procedure which suits the individual demand at the highest degree.

The presented work demonstrates the most suitable architecture for the FPGA-based signal processing which makes available various real-time filtering algorithms, such as band pass, high pass, low pass, and band-reject for FIR filters. The processor was implemented with the fixed-point arithmetic using VHDL, which can be downloadable on FPGA device. The FPGA device can be interfaced with an analog-to-digital converter (ADC), digital-to-analog converter (DAC) and a personal computer with MATLAB for the user interface and feeding coefficients and order of the filter. The core part of this paper was to find the reconfigurable and efficient architecture of the processor with only one multiplier which can work for Finite Impulse response (FIR) filter with the best-suited structure. The system will be used for automatic generation of fixed-point FIR filters. The model was also implemented in MATLAB script and the verification of results in the case of low-pass filtering confirmed that both models in MATLAB and VHDL matched to each other. All components of architecture in VHDL were designed using generics which allow changing its structure and behavior by generic values. Therefore, it is a universal filter platform where user can process the data while changing the filter parameters as per the requirement of applications. The complete design was verified by taking the example of audio signal frequency, but parameterized components of system architecture can also facilitate its applicability at ultrasonic frequencies by changing the algorithm. The significance and applicability of FPGAs in ultrasonic signal processing were also studied and reviewed. . He also works as a Lecturer at Multimedia Engineering Department of Kaunas University of Technology. He also achieved Master degree in Electronics engineering (VLSI) at University of Westminster, London, England in 2011. His current research includes development of signal and image processing methods, ultrasonic NDT of composite materials etc. Armantas Ostreika received Ph.D. degree in information technology at Kaunas University of Technology, Lithuania in 2000. He is head of Multimedia Engineering Department at Kaunas University of Technology. His current research includes digital image processing, statistical image analysis, object recognition and interpretation, image restoration, stereo and multi-view imaging, digital photogrammetric systems, video processing etc. Jūratė Platužienė received Master degree in information technology at Kaunas University of technology. She is a Lecturer at Multimedia Engineering Department of Kaunas University of Technology. The main scope of her activity is computer graphics and 3D modeling and animation.