Experimental Proposal with Mallows Distribution Applied to the Mixed No-Idle Permutation Flowshop Scheduling Problem
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Publisher
Springer Nature Switzerland
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https://link.springer.com/content/pdf/10.1007/978-3-031-28999-6_28
Reference21 articles.
1. Pan, Q.-K. (2014). An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem. Omega, 44, 41–50.
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3. Ceberio, J. (2014). A distance based ranking model estimation of distribution algorithm for the flow shop scheduling problem. IEEE Transactions on Evolutionary Computation, 18(2), 286–299.
4. Murilo Zangari, A. M. (2017). Multiobjective decomposition-based Mallows Models estimation of distribution algorithm. A case of study for permutation flowshop scheduling problem. In Information Sciences, 137–154.
5. Ricardo Pérez-Rodríguez, A. H.-A. (2019). A hybrid estimation of distribution algorithm for the vehicle routing problem with time windows. Computers and Industrial Engineering, 130, 75–96.
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1. A Systematic Literature Review on No-Idle Flow Shop Scheduling Problem;Operations Research Forum;2024-02-27
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