Journal article
Heuristic production triggering mechanisms under discrete unequal inventory withdrawals
International journal of production economics, v 45(1), pp 83-90
1996
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The existing literature on inventory control has largely ignored the timing issue concerning inventory replenishment under discrete demand, occurring in sizeable lot quantities at irregular intervals. Such demand patterns are not uncommon in industrial purchasing situations, where customers buy products, based on their own purchase lot sizing policies, from wholesalers or commercial vendors. This paper specifically addresses the question of designing mechanisms for triggering setups of replenishment production lots of a product, which is sold to several commercial customers in a stochastic environment and is manufactured in a batch production facility, strictly from the vendor's perspective. Due to the analytical difficulties in the statistical modeling of stochastic demand patterns described above, we develop several heuristics, based on both continuous and periodic inventory review, for the purpose of signalling the startup of a production batch. The effectiveness of these heuristic procedures are tested through a series of simulation experiments.
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Details
- Title
- Heuristic production triggering mechanisms under discrete unequal inventory withdrawals
- Creators
- Avijit Banerjee - Drexel UniversityJonathan Burton - Drexel UniversitySnehamay Banerjee - Drexel University
- Publication Details
- International journal of production economics, v 45(1), pp 83-90
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:A1996VP43700011
- Scopus ID
- 2-s2.0-0030205775
- Other Identifier
- 991019168906604721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Industrial
- Engineering, Manufacturing
- Operations Research & Management Science