Throughput Control and Revenue Optimization of a Poultry Product Batcher

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Abstract

This article studies the optimal control of batching equipment in the poultry processing industry. The problem is to determine a control policy that maximizes the long-term average revenue while achieving a target throughput. This problem is formulated as a Markov Decision Process (MDP). The developed MDP model captures the unique characteristics of poultry processing operations, such as, the trade-off between giveaway and throughput. Structural properties of the optimal policy are derived for small-sized problems where batching equipment utilizes a single bin. Since the MDP model is numerically intractable for industry-sized problems, we propose a heuristic index policy with a Dynamic Rejection Threshold (DRT). The DRT heuristic is constructed based on the salient characteristics of the problem setting and is easy to implement in practice. Numerical experiments demonstrate that DRT performs well. We present an industry case study where DRT is benchmarked against current practice, which shows that the expected revenue can be potentially increased by over 2% (yielding an additional revenue between 750,000 and 2,270,000 Euros per year) through the use of DRT.

Original languageEnglish
Pages (from-to)845-857
Number of pages13
JournalIISE Transactions
Volume54
Issue number9
DOIs
Publication statusPublished - Sep 2022

Keywords

  • Bin-covering problem
  • Markov decision processes
  • case study
  • index policies

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