Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/178281 
Year of Publication: 
2017
Citation: 
[Journal:] Operations Research Perspectives [ISSN:] 2214-7160 [Volume:] 4 [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2017 [Pages:] 123-135
Publisher: 
Elsevier, Amsterdam
Abstract: 
In this paper we describe the automatic instantiation of a Variable Neighborhood Descent procedure from a Mixed Integer Programming model. We extend a recent approach in which a single neighborhood structure is automatically designed from a Mixed Integer Programming model using a combination of automatic extraction of semantic features and automatic algorithm configuration. Computational results on four well-known combinatorial optimization problems show improvements over both a previous model-derived Variable Neighborhood Descent procedure and the approach with a single automatically-designed neighborhood structure.
Subjects: 
Mixed Integer Programming
Variable Neighborhood Descent
Semantic features
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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