Smarter scheduling for seafood processing

We are pleased to announce a new OR&S publication in Flexible Services and Manufacturing Journal: Servranckx, T., Verbanck, T., Song, J., & Vanhoucke, M. (2026). A genetic algorithm for seafood processing with flexible flow shops and sequence-dependent setups. Flexible Services and Manufacturing Journal, 38, 650–689.

This research addresses a real-life production planning problem in the seafood industry. At a large Belgian seafood processing company, products first pass through a preparation stage and are then packaged on parallel packaging lines. While this production process may appear straightforward, creating an efficient schedule is far from easy. Packaging different seafood products often requires changing moulds, gas compositions or packaging formats, resulting in sequence-dependent setup times. Moreover, because seafood is highly perishable, products should move through the production process as quickly as possible to preserve freshness and quality.

The paper develops advanced optimisation techniques to improve the planning of this production process. The authors model the problem as a flexible flow shop scheduling problem with sequence-dependent setup times and multiple practical objectives. Besides minimising the overall production time (makespan), the proposed methods also account for objectives that were considered important by the company's management, making the research directly applicable in practice.

To solve these complex scheduling problems, the researchers developed a tailored genetic algorithm. Unlike generic optimisation approaches, this algorithm incorporates problem-specific crossover and mutation operators together with mechanisms to maintain population diversity. Computational experiments on real industrial data, involving more than one hundred customer orders per day, demonstrate that the proposed approach produces high-quality schedules within practical computation times, outperforming simpler scheduling procedures while remaining suitable for industrial implementation.

This publication is also an excellent example of OR&S's close integration of education and research. The work originated from the Master's thesis of Thibault Verbanck, who continued developing the research into a full scientific publication. The project was also carried out in collaboration with Jie Song, an OR&S member who is currently conducting research in China, illustrating the international nature of our research collaborations.

The study contributes both to scheduling theory and to industrial practice by illustrating how advanced optimisation methods can improve efficiency in food production without compromising product quality. It also shows the value of combining academic research with real industrial case studies to develop algorithms that are not only theoretically strong but also practically deployable.

We are particularly pleased to see a Master's thesis evolve into a peer-reviewed journal publication and hope this inspires future students to pursue research with real industrial impact.