Optimising replenishment policy in an integrated supply chain with controllable lead time and backorders-lost sales mixture

This paper aims to optimise the inventory replenishment policy in an integrated supply chain consisting of a single supplier and a single buyer. The system under consideration has the features such as backorders-lost sales mixture, controllable lead time, stochastic demand, and stockout costs. The underlying problem has not been studied in the literature. The authors present a novel approach to formulate the optimisation problem, which is able to satisfy the constraint on the number of admissible stockouts per time unit. To solve the optimisation problem, the authors propose two algorithms: an exact algorithm and a heuristic algorithm. These two algorithms are developed based on some analytical properties that the authors established by analysing the cost function in relation to the decision variables. The heuristic algorithm employs an approximation technique based on an ad-hoc Taylor series expansion. Extensive numerical experiments are provided to demonstrate the effectiveness of the proposed algorithms.

• Record URL:
  https://doi.org/10.1504/IJLSM.2018.090474
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/17427967
• Supplemental Notes:
  • Copyright © 2018 Inderscience Enterprises Ltd.
• Authors:
  • Braglia, Marcello
  • Castellano, Davide
  • Song, Dongping
• Publication Date: 2018

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 476-501
• Serial:
  • International Journal of Logistics Systems and Management
  • Volume: 29
  • Issue Number: 4
  • Publisher: Inderscience Enterprises Limited
  • ISSN: 1742-7967
  • EISSN: 1742-7945
  • Serial URL: http://www.inderscience.com/jhome.php?jcode=ijlsm

Subject/Index Terms

• TRT Terms: Algorithms; Demand; Heuristic methods; Lead time; Optimization; Sales; Stochastic processes; Supply chain management
• Uncontrolled Terms: Shelf replenishment; Stochastic demand
• Subject Areas: Administration and Management; Freight Transportation; Operations and Traffic Management; Planning and Forecasting; Policy;

Filing Info

• Accession Number: 01667738
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 30 2018 9:20AM