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\iteman{io-port 05983328}
\itemau{Sierra, Mar{\'\i}a R.; Menc{\'\i}a, Carlos; Varela, Ramiro}
\itemti{Optimally scheduling a job-shop with operators and total flow time minimization.}
\itemso{Lozano, Jose A. (ed.) et al., Advances in artificial intelligence. 14th conference of the Spanish association for artificial intelligence, CAEPIA 2011, La Laguna, Spain, November 7--11, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-25273-0/pbk). Lecture Notes in Computer Science 7023. Lecture Notes in Artificial Intelligence, 193-202 (2011).}
\itemab
Summary: We face the job-shop problem with operators and total flow time minimization. This problem extends the classical job-shop problem by considering a limited number of operators that assist the processing of the operations. We propose a schedule generation scheme that extends the well-known G\&T algorithm. This scheme is then exploited to design an any-time algorithm that combines best-first and greedy search and takes profit from two monotonic heuristics and a method for pruning states based on dominance relations. The results of an experimental study across several benchmarks show that our approach outperforms a constraint programming approach.
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\itemli{doi:10.1007/978-3-642-25274-7\_20}
\end