Multi-criteria inventory classification problem: An effective artificial immune algorithm

In this paper, we study the problem of multi-criteria ABC inventory
classification using an efficient artificial immune algorithm (AIA) to
partially alter the traditionally incomprehensive attitude of single
objective consideration of inventory control problems. Therefore, we
simultaneously endeavor to investigate two different subjects. First, we
incorporate various criteria such as annual dollar usage, lead time,
criticality, commonality, obsolescence and substitutability into the
problem of ABC inventory classification. This method is regarded in lieu
of mere consideration of the annual dollar usage criteria in the traditional
ABC inventory classification. Second, the proposed AIA delays the
algorithm convergence due to its restraining mechanism; meanwhile, it
alleviates the problem of premature convergence of existing genetic
algorithm to end up with more precise ABC inventory classification.
Finally, we draw an analogy between the results obtained from both
algorithms applied to a real case study present in the literature. The
superiority and effectiveness of our AIA is inferred from all the results
obtained in various situations
Inventory management, Multi-criteria analysis; ABC classification; Artificial immune algorithm

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