Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/130539
Author(s): S. Mahdi Homayouni
Dalila M. M. Fontes
Fernando A. C. C. Fontes
Title: A Biased Random Key Genetic Algorithm for the Flexible Job Shop Problem with Transportation
Issue Date: 2019
Abstract: This work addresses the Flexible Job Shop Scheduling Problem with Transportation resources (FJSPT), which can be seen as an extension of both the Flexible Job Shop Scheduling Problem (FJS) and the Job Shop Scheduling Problem with Transportation resources (JSPT). Regarding the former case, the FJSPT additionally considers that the jobs need to be transported to the machines they are processed in; while regarding the latter, in the FJSP the specific machine processing each operation also needs to decided. The FJSPT is NP-hard since, it extends NP-hard problems. In here, we propose an operation based biased random key genetic algorithm to efficiently find good quality solutions.
URI: https://hdl.handle.net/10216/130539
Source: XIII Metaheuristics International Conference MIC
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: restrictedAccess
Appears in Collections:FEP - Artigo em Livro de Atas de Conferência Internacional
FEUP - Artigo em Livro de Atas de Conferência Internacional

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