You have no items in your shopping cart.

Roqueta Origen: Streamlining Wine Storage and Mixing (A)
Biggs, Max; Baucells, Manel; Alizamir, Saed; Klopfenstein, Amy Case QA-0978 / Published August 26, 2024 / 5 pages. Collection: Darden School of Business
Format Price Quantity Select
PDF Download
$6.95
Printed Black & White Copy
$7.25

Product Overview

This case examines an allocation problem at Roqueta Origen, a Spanish winery. A consultant must determine which batches of different wines to assign to tanks for maturation. As she considers which wines to allocate to different tanks, she must consider factors such as the wine quality, grape variety, vintage, and wine color. She aims to allocate the wines to achieve the highest possible wine quality and will also ideally avoid over-filling or under-filling the tanks.



Learning Objectives

- Identify and evaluate the advantages and disadvantages of different optimization formulations for a complex real-world scenario without a clearly dominant solution. - Learn how to communicate with and manage analysts with optimization expertise. - Understand how to formulate nonlinear mixing problems and linearize nonlinear terms using binary variables. - Appreciate that sometimes a sequence of simple optimization problems can approximate and outperform a more complex model. - Understand how optimization techniques can be applied to improve operational efficiency in horticulture. - Interrogate solution output to evaluate model performance. - Learn how mathematical notation is used to communicate and formalize optimization formulations. - Appreciate what makes an optimization formulation easy or difficult to solve. - (Optional) Consider how we can use large language models (LLMs) to help us prototype and solve optimization problems. - (Optional) Learn how to use Gurobi and Python to solve large-scale optimization problems.


  • Videos List

  • Overview

    This case examines an allocation problem at Roqueta Origen, a Spanish winery. A consultant must determine which batches of different wines to assign to tanks for maturation. As she considers which wines to allocate to different tanks, she must consider factors such as the wine quality, grape variety, vintage, and wine color. She aims to allocate the wines to achieve the highest possible wine quality and will also ideally avoid over-filling or under-filling the tanks.

  • Learning Objectives

    Learning Objectives

    - Identify and evaluate the advantages and disadvantages of different optimization formulations for a complex real-world scenario without a clearly dominant solution. - Learn how to communicate with and manage analysts with optimization expertise. - Understand how to formulate nonlinear mixing problems and linearize nonlinear terms using binary variables. - Appreciate that sometimes a sequence of simple optimization problems can approximate and outperform a more complex model. - Understand how optimization techniques can be applied to improve operational efficiency in horticulture. - Interrogate solution output to evaluate model performance. - Learn how mathematical notation is used to communicate and formalize optimization formulations. - Appreciate what makes an optimization formulation easy or difficult to solve. - (Optional) Consider how we can use large language models (LLMs) to help us prototype and solve optimization problems. - (Optional) Learn how to use Gurobi and Python to solve large-scale optimization problems.