REPLENISHMENT POLICY FOR A PROCESSING SYSTEM WITH STOCHASTIC CONSTRAINTS, DISCOUNT AND IMPERFECT ITEMS
DOI:
https://doi.org/10.52292/j.laar.2021.211Keywords:
Genetic algorithm, GRASP, Inventory Control, Stochastic constraintsAbstract
In this paper, a processing system with multiple products, single-vendor and single-buyer is considered to maximize the inventory system’s profit. In order to be more suit for real-world applications, this model contains five stochastic constraints including backordering cost, space, ordering, procurement, and available budget. It is assumed that orders are subjected to quantity discount and also imperfect goods are permitted. The price of the perfect and imperfect goods are assumed to be different. The imperfect goods are assumed to be returned to the system for rework process. The objective is to find the optimal order quantities of products such that the total inventory profit to be maximized while satisfying all the constraints. The problem is formulated as a mixed integer nonlinear programming problem. Two algorithms, based on GA and GRASP are developed to solve the resulting model. Performance of the algorithms are analyzed based on 45 numerical examples with different sizes.
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