A Parallel Variable Neighborhood Search for Solving Real-World Production-Scheduling Problems

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Springer Science and Business Media Deutschland GmbH
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In recent years, industry has evolved towards the efficient digitalization and optimization of products and processes. This situation is the consequence of the huge amount of information available in indus trial environments and its efficient management for reaching unprece dented productivity levels. The momentum that enjoys this application field has led to the proposal of advanced methods for the dealing of robotic processes in industrial plants, optimal packaging of goods and the efficient scheduling of production plans, among many others. This paper is focused on the last of these categories. More concretely, we present a Parallel Variable Neighborhood Search for solving an industrial problem in which a fixed amount of materials should be constructed into a limited number of production lines. The construction of these materials has sev eral particularities, such as the need of some specific tools to be correctly produced. It is also relevant to underscore that the problem solved in this research corresponds to a real-world situation, and that it is currently deployed in a production plant in the Basque Country (Spain).
Osaba, Eneko, Erlantz Loizaga, Xabier Goenaga, and Valentin Sanchez. “A Parallel Variable Neighborhood Search for Solving Real-World Production-Scheduling Problems.” Lecture Notes in Computer Science (2021): 12–20. doi:10.1007/978-3-030-91608-4_2.