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• W2897619499 abstract "Abstract A shortage may occur because of the insufficient production capacity or possible damages of items in transit, and the shortage can be partially fulfilled with substitutable items. In this study, a joint replenishment problem (JRP) with the shortage and partial demand substitution is investigated by developing a mixed integer nonlinear programming model. Several real-world constraints, such as budget, transportation capacity, and shipment requirement constraints are incorporated in the proposed model. Three heuristic algorithms, namely two-dimensional genetic algorithm I, two-dimensional genetic algorithm II, and differential evolution, are proposed, and numerical examples are provided to demonstrate the applicability of the proposed model in a real-world setting. The performance of the heuristic algorithms is investigated with the help of extensive computational experiments. The results show that differential evolution performs best in term of the minimum total cost among three heuristics. Sensitivity analyses are conducted to provide managerial insights. The results indicate that partial demand substitution policy can effectively decrease the total expected cost, but defective items will exponentially increase the total expect cost. The major ordering cost, budget, and truck capacity also affect the system." @default.
• W2897619499 created "2018-10-26" @default.
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• W2897619499 date "2019-01-01" @default.
• W2897619499 modified "2023-09-24" @default.
• W2897619499 title "Joint replenishment decision considering shortages, partial demand substitution, and defective items" @default.
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• W2897619499 doi "https://doi.org/10.1016/j.cie.2018.10.031" @default.
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