Abstract
The fishing industry is one of the main contributors to the national economy, value creation, and employment in
Norway. Furthermore, it is a significant source of export incomes. The fishing industry is also a well-known arena for
applying operations research methodology. Traditionally divided in three main parts, the works within this area have
dealt with fish stock and harvesting, fish processing, and marketing. Recently, the focus has shifted to integrated
planning, where fishing fleet operations are combined with plant processing. Currently, a broader view of the supply
chain needs to be adopted as many companies in this industrial sector are striving to improve their capacity
utilizations, operational efficiency, and profitability. Thus, both upstream and downstream uncertainties need to be
handled directly. While it has been recognized that decision flexibility can be used to manage supply chain
uncertainty, no known stochastic modeling formulations have explicitly accounted for it in fish processing.
To address the described planning challenges, this paper develops a stochastic model, incorporating both upstream
(raw material quantities) and downstream (finished goods prices) uncertainties, while accounting for fish quality
deterioration and shelf-life restrictions. The model is used on a number of case studies, estimating the value of
flexibility in the supply chain provided by the introduction of super-chilling technologies and application of the
described stochastic formulation. This way, it reflects a triangulation of technological development, operational
efficiency, and market profitability. Thus, it is a unique opportunity to address the real-world complexity and enhance
the body of knowledge in operations research.
Norway. Furthermore, it is a significant source of export incomes. The fishing industry is also a well-known arena for
applying operations research methodology. Traditionally divided in three main parts, the works within this area have
dealt with fish stock and harvesting, fish processing, and marketing. Recently, the focus has shifted to integrated
planning, where fishing fleet operations are combined with plant processing. Currently, a broader view of the supply
chain needs to be adopted as many companies in this industrial sector are striving to improve their capacity
utilizations, operational efficiency, and profitability. Thus, both upstream and downstream uncertainties need to be
handled directly. While it has been recognized that decision flexibility can be used to manage supply chain
uncertainty, no known stochastic modeling formulations have explicitly accounted for it in fish processing.
To address the described planning challenges, this paper develops a stochastic model, incorporating both upstream
(raw material quantities) and downstream (finished goods prices) uncertainties, while accounting for fish quality
deterioration and shelf-life restrictions. The model is used on a number of case studies, estimating the value of
flexibility in the supply chain provided by the introduction of super-chilling technologies and application of the
described stochastic formulation. This way, it reflects a triangulation of technological development, operational
efficiency, and market profitability. Thus, it is a unique opportunity to address the real-world complexity and enhance
the body of knowledge in operations research.