Subhasis Das
Dr. Anindya Ghosh
Dr. Abhijit Majumdar
Dr. Debamalya Banerjee
Abstract
This paper presents an idea to combine Genetic Algorithm (GA) optimization heuristic with TOPSIS multi-criteria decision making method to render it an optimization capability in a multi criteria setting. The relative importance or weights ofdifferent fibre criteria for the selection ofraw materials i.e. cotton fibres in textile spinning industry are determined using the hybrid GA-TOPSIS method. Six quality parameters of fibres viz., strength, elongation, upper half mean length, length uniformity, fineness and shortfibre content are regarded as the criteria for cotton selection in an attempt to achieve maximum strength of the yarn. GA has been applied to search the optimum set of weights for various cotton fibre criteria by means of maximizing the rank correlation coefficient obtaining from the two methods of ranking such as TOPSIS quality index of different types of cottons and strength of the yarns spun from them. The investigation indicates that the criteria weights for cotton selection can be obtained with a reasonable degree of agreement. The obtained weights signify the actual contribution of different cotton fibre properties on yarn strength. The result shows that the fibre strength has maximum contribution on yarn strength followed by fibre length parameters and fineness. Fibre elongation has least contribution on yarn strength. The proposed approach is flexible and can be modified with ease depending upon the technology of spinning being followed in the industry. Moreover, it can universalize itself into the far wider domain of multi-criteria decision making problems.
Keywords- Cotton, genetic algorithm, raw material, spinning industry, TOPSIS.