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    Multi-Objective Optimization of Slow Moving Inventory System Using Cuckoo Search

    Achin Srivastav, Sunil Agrawal

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 343-350, 2018, DOI:10.1080/10798587.2017.1293891

    Abstract This paper focuses on the development of a multi-objective lot size–reorder point backorder inventory model for a slow moving item. The three objectives are the minimization of (1) the total annual relevant cost, (2) the expected number of stocked out units incurred annually and (3) the expected frequency of stockout occasions annually. Laplace distribution is used to model the variability of lead time demand. The multi-objective Cuckoo Search (MOCS) algorithm is proposed to solve the model. Pareto curves are generated between cost and service levels for decision-makers. A numerical problem is considered on a slow moving item to illustrate the… More >

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