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|Title:||Beer Game Order Policy Optimization Using Genetic Algorithms|
|Authors:||BOSCH PAGANS Jordi; STROZZI Fernanda; ZALDIVAR COMENGES JOSE'|
|Publisher:||Carlo Cattaneo University|
|JRC Publication N°:||JRC32232|
|Type:||Articles in books|
|Abstract:||In this work we analyse the optimal order policies, i.e. the optimal parameters of the Sterman model, when a step-change occurs in the customer demand. The optimal policy considered is the policy that gives the minimum cost, accounting both for the costs to maintain a stock of goods and for the costs of having a backlog when it is not possible to satisfy the demand. Two scenarios have been analysed: all sectors apply the same order policies, or different policies are applied from sector to sector. The search of the optimal solution has been performed using Genetic Algorithms due to the complexity of the objective cost function, which has many local minima and, in the case of different policies, many parameters.|
|JRC Institute:||Institute for Environment and Sustainability|
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