Coordinating supply-chain management under stochastic fuzzy environment and lead-time reduction

Asif Iqbal Malik, Biswajit Sarkar

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

In this paper, a supply-chain (SC) coordination method based on the lead-time crashing is proposed for a seller-buyer system. By considering different transportation modes, we control the lead-time (LT) variability. For the first time, we have attempted to determine the impact of the reliable and unreliable seller in a continuous-review supply-chain model under the stochastic environment. The authors discussed two reliability cases for the seller. First, we consider the seller is unreliable and in the second case, the seller is reliable. In addition, the demand during the lead time is stochastic with the known mean and variance. The proposed approach tries to find an optimal solution that performs well without a specific probability distribution. Besides, a discrete investment is made to reduce the setup cost, which will indirectly help supply-chain members to increase the total profit of the system. In the proposed model, the seller motivates the buyer by reducing lead time to take part in coordinating decision-making for the system's profit optimization. We derive the coordination conditions for both members, the seller and the buyer, under which they are convinced to take part in the cooperative decision-making plan. Therefore, lead-time crashing is the proposed incentive mechanism for collaborative supply-chain management. We use a fixed-charge step function to calculate the lead-time crashing cost for slow and fast shipping mode. We give two numerical examples to validate the proposed models and demonstrate the service-level enhancement under the collaborative supply-chain management in case of an unreliable seller. Concluding remarks and future extensions are discussed at the end.

Original languageEnglish
Article number480
JournalMathematics
Volume7
Issue number5
DOIs
Publication statusPublished - 2019 Jan 1

All Science Journal Classification (ASJC) codes

  • Mathematics(all)

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