A design procedure for a dual feed network is presented to produce a circular polarised matched antenna involving eight design parameters with associated constraints. Determination of such design parameters has been m...
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A design procedure for a dual feed network is presented to produce a circular polarised matched antenna involving eight design parameters with associated constraints. Determination of such design parameters has been made possible by utilising a multiobjective genetic algorithm (MGA) approach. The conditions For circular polarisation and impedance matching were the objective functions employed in the MGA. The associated constraints were the lengths and characteristic impedance values of the feed network. The return loss and axial ratio for a 5.8GHz antenna were investigated and good agreement was obtained between simulated and practical measurements.
In this paper, a multi-objective geneticalgorithm to solve assembly line balancing problems is proposed. The performance criteria considered are the number of workstations, the line efficiency, the smoothness index b...
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In this paper, a multi-objective geneticalgorithm to solve assembly line balancing problems is proposed. The performance criteria considered are the number of workstations, the line efficiency, the smoothness index before trade and transfer, and the smoothness index after trade and transfer. The developed geneticalgorithm is compared with six popular heuristic algorithms, namely, ranked positional weight, Kilbridge and West, Moodie and Young, Hoffmann precedence matrix, immediate update first fit, and rank and assign heuristic methods. For comparative evaluation, 20 networks are collected from open literature, and are used with five different cycle times. All the six heuristics and the geneticalgorithm are coded in C++ language. It is found that the proposed geneticalgorithm performs better in all the performance measures than the heuristics. However, the execution time for the GA is longer, because the GA searches for global optimal solutions with more iterations.
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