Revealing risk mitigation strategies for supply chain resilience in aquaculture industry through a methodology equipped with lean tools and stochastic programming

With a notable focus on seafood, especially salmon, which is crucial for global food security, substantial investments have fueled the growth of Turkish salmon farming in the Black Sea region. Despite being profitable, the industry faces challenges, including supply chain vulnerabilities to internal and external disruptions, leading to a ripple effect. One of the most significant challenges in the sector is fish escapes, which directly impact lead time and customer satisfaction levels. By specifically focusing on undercurrent and storm factors, this study proposes a comprehensive methodology, adopting a continuous improvement cycle to manage this challenge. This methodology involves a novel scenario-based two-stage stochastic programming model with the objective of minimizing the expected overall cost. The model is formulated for the transportation problem, addressing fish escapes within the aquaculture industry to establish a resilient supply chain structure. It also explores the comprehensiveness of lean implementation associated with various reliability levels, representing the decision-maker’s risk propensity. Moreover, a design of experiment (DoE) setting is established to scrutinize the impact of controlled factors and their interactions on the outcomes. After conducting computational analysis, considering the impact of factors, lean maturity levels, and the comprehensiveness of lean implementation on the results, valuable managerial insights are provided within the context of risk mitigation strategies. The findings indicate that in the event of severe disruptions, significant improvements in risk mitigation can be achieved through the continuous improvement-based methodology, primarily driven by lean tools.