{'fraction_non_alphanumeric': 0.017355371900826446, 'fraction_numerical': 0.0, 'mean_word_length': 5.653846153846154, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Metaheuristic Techniques to Optimize the Steaming Process of Elastic Denim Yarns

ABSTRACT The elastic yarns are complex structures that are not easily controllable especially at the time of the severe requests because of their heterogeneous compositions. Optimizing the yarn properties after steaming process is important for the industrial and user’s viewpoint, because it affects the quality of the yarn and the garment’s characteristics as the appearance and the mechanical properties. Genetic Algorithms (GA) and Ant Colony Optimization (ACO) are applied to optimize the strength at break of elastic denim yarns before and after steaming. Indeed, some influential input parameters such as the linear density of elastane filament type Spandex©, the steaming process, the relaxation durations and the temperature during steaming were investigated to analyze their contributions on the mechanical property, breaking strength or kilometric resistance (). To study the input parameter contributions and to evaluate objectively the behavior, an experimental design type Taguchi analysis was used. The results show that there is a good relationship between the elastic denim yarn behavior and the studied inputs.