A new model for the One-dimensional Cutting Stock problem using Genetic Algorithms (GA) is developed to optimize construction steel bars waste. One-dimensional construction stocks (i.e., steel rebars, steel sections, dimensional lumber, etc.) are one of the major contributors to the construction waste stream. Construction wastes account for a significant portion of municipal waste stream. Cutting one-dimensional stocks to suit needed project lengths results in trim losses, which are the main causes of one-dimensional stock wastes. The model developed and the results obtained were compared with real life case studies from local steel workshops. Cutting schedules produced by our new GA model were tested in the shop against the current cutting schedules. The comparisons show the superiority of this new GA model in terms of waste minimization.
A second-generation autonomous music composition tool is developed using Genetic Algorithms. The composition is conducted in two Stages. The first Stage generates and identifies musically sound patterns (motifs). In the second Stage, methods to combine different generated motifs and their transpositions are applied. These combinations are evaluated and as a result, musically fit phrases are generated. Four musical phrases are generated at the end of each program run. The generated music pieces will be translated into Guido Music Notation (GMN) and have alternate representation in Musical Instrument Digital Interface (MIDI). The Autonomous Evolutionary Music Composer (AEMC) was able to create interesting pieces of music that were both innovative and musically sound.
This paper presents a novel approach for a free structure analog circuit design using Genetic Algorithms (GA). A major problem in a free structure circuit is its sensitivity calculations as a polynomial approximation for the design is not available. A further problem is the effect of parasitic elements on the resulting circuit's performance. In a single design stage, circuits are produced that satisfy a specific frequency response specifications using circuit structures that are unrestricted and with component values that are chosen from a set of preferred values including their parasitic effects. The sensitivity to component variations for the resulting designs is performed using a novel technique and is incorporated in the fitness evaluation function. The extra degrees of freedom resulting form unbounded circuit structures create a huge search space. The application chosen is a LC all pass ladder filter circuit design.
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