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Fishing policies in a supply chain with an organic waste-based side stream

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  • Kogan, Konstantin
  • Perlman, Yael
  • Shatz, Smadar

Abstract

Organic waste resulting from fishing—consisting primarily of inedible fish parts and bycatch (non-target species) discarded during on-shore processing—is a source of substantial ecological concern. Researchers and practitioners are increasingly exploring how fishing supply chains can convert such waste into profitable products, towards benefiting the environment and the economy. The current study puts forward an optimal control model that addresses interactions between fishing practices, fish populations, and waste streams from fishing operations, with the aim of understanding how to achieve profitable and environmentally sustainable fishing practices. Although numerous models have been proposed for optimizing fish population management, ours is among the first to incorporate waste-processing dynamics, providing insight into how dynamic interactions between main-stream and side-stream supply chain operations can affect fishing policies and the overall ecosystem. We derive a necessary condition for sustainability of a “green” supply chain (i.e., one that incorporates side-stream processing) and determine the maximum fishing effort to ensure that a steady-state fish stock exists. We prove that when the cost of fish harvesting is negligible, a green supply chain (vs. a supply chain without side-stream processing) significantly reduces the rate of waste disposal but does not improve the stock of fish biomass. In a numerical analysis, we show that this result holds even when harvesting costs are high. The numerical analysis also shows that a sufficient increase in the marginal cost of fishing eliminates potential multiplicity of the steady states, thereby improving fish stock stability and ecosystem health.

Suggested Citation

  • Kogan, Konstantin & Perlman, Yael & Shatz, Smadar, 2024. "Fishing policies in a supply chain with an organic waste-based side stream," European Journal of Operational Research, Elsevier, vol. 316(2), pages 651-666.
  • Handle: RePEc:eee:ejores:v:316:y:2024:i:2:p:651-666
    DOI: 10.1016/j.ejor.2024.02.014
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