Abstract
In the lobster processing industry, savvy decision-makers call for robust, fast, and cheap decision support systems to simulate scenarios in hard-to-predict market conditions for planning sales and operations of the next season. For optimizing the planning of simulated scenarios, linear programming models are customized to the constraints of each business case, and to data readily available from past seasons. For illustration, two significantly different cases are presented with results. Considerations regarding cross training and cell operations is discussed to resolve shifting bottlenecks and consequently improve financial performance. Depending on cases, direct margins could be improved by up to two-digit rates.
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