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Mattia Neroni, Massimo Bertolini and Angel A. Juan
In automated storage and retrieval systems (AS/RSs), the utilization of intelligent algorithms can reduce the makespan required to complete a series of input/output operations. This paper introduces a simulation optimization algorithm designed to minimiz...
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Juliana Castaneda, Mattia Neroni, Majsa Ammouriova, Javier Panadero and Angel A. Juan
Many real-life combinatorial optimization problems are subject to a high degree of dynamism, while, simultaneously, a certain level of synchronization among agents and events is required. Thus, for instance, in ride-sharing operations, the arrival of veh...
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Christoph Laroque, Madlene Leißau, Pedro Copado, Christin Schumacher, Javier Panadero and Angel A. Juan
Based on a real-world application in the semiconductor industry, this article models and discusses a hybrid flow shop problem with time dependencies and priority constraints. The analyzed problem considers a production where a large number of heterogeneo...
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Christin Schumacher and Peter Buchholz
In modern production systems, scheduling problems have to be solved in consideration of frequently changing demands and varying production parameters. This paper presents a approach combining forecasting and classification techniques to predict uncertain...
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Atif Shahzad and Nasser Mebarki
A promising approach for an effective shop scheduling that synergizes the benefits of the combinatorial optimization, supervised learning and discrete-event simulation is presented. Though dispatching rules are in widely used by shop scheduling practitio...
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