EURO 2025 Leeds
Abstract Submission

2593. Optimizing Seafood Supply Chains: Minimize Food Loss and Waste by Integrating Vessel Routing, Scheduling, and Energy Usage

Invited abstract in session TB-17: Novel applications in warehousing, maritime transport, and healthcare, stream Combinatorial Optimization.

Tuesday, 10:30-12:00
Room: Esther Simpson 2.08

Authors (first author is the speaker)

1. Chiara Maragò
Department of Mechanical, Energy, and Management Engineering (DIMEG), University of Calabria
2. Ali Ghavamifar
Department of Technology, Management and Economics, Technical University of Denmark
3. Dario Pacino
Department of Management, Technology and Economics, Technical University of Denmark
4. Allan Larsen
Department of Management, Technology and Economics, Technical University of Denmark
5. Francesca Guerriero
D.I.M.E.G.: Mechanical, Energy and Management Engineering, University of Calabria
6. Rosita Guido
Department of Mechanical, Energy and Management Engineering, University of Calabria

Abstract

The fishing industry operates under complex and dynamic conditions, facing multiple challenges such as uncertainty in fish availability, fluctuating fuel prices, catch quotas, seasonal variations, quality preservation constraints, and sustainability standards. This study develops an optimization model aimed at maximizing the income of an Icelandic fishing company by holistically integrating vessel routing, scheduling, and production decisions. To enhance decision-making, we incorporate fish quality considerations into the model, recognizing their impact on both profitability and energy consumption during processing. We propose a mixed-integer programming (MIP) model that accounts for these interconnected tactical-level decisions while incorporating industry-specific constraints. To address the uncertainty in fish availability, we generate multiple scenarios to represent potential catch locations and supply variability. Given the computational complexity of the problem, we apply a heuristic solution approach to support the company's decision-making process. This data-driven framework integrates critical operational factors to enhance efficiency, reduce costs, and promote sustainability in fisheries management. By optimizing fisheries supply chains, our results provide valuable insights for improving profitability and sustainable practices while ensuring compliance with regulatory constraints.

Keywords

Status: accepted

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