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109 results on '"Fontes, Dalila B. M. M."'

1. A Multi-Population BRKGA for Energy-Efficient Job Shop Scheduling with Speed Adjustable Machines

Author

Homayouni, S. Mahdi, Fontes, Dalila B. M. M., Fontes, Fernando A. C. C., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Di Gaspero, Luca, editor, Festa, Paola, editor, Nakib, Amir, editor, and Pavone, Mario, editor

Published
2023
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3. Energy-Efficient Scheduling of Intraterminal Container Transport

Author

Homayouni, S. Mahdi, Fontes, Dalila B. M. M., Pardalos, Panos M., Series Editor, Thai, My T., Series Editor, Du, Ding-Zhu, Honorary Editor, Belavkin, Roman V., Advisory Editor, Birge, John R., Advisory Editor, Butenko, Sergiy, Advisory Editor, Kumar, Vipin, Advisory Editor, Nagurney, Anna, Advisory Editor, Pei, Jun, Advisory Editor, Prokopyev, Oleg, Advisory Editor, Rebennack, Steffen, Advisory Editor, Resende, Mauricio, Advisory Editor, Terlaky, Tamás, Advisory Editor, Vu, Van, Advisory Editor, Vrahatis, Michael N., Associate Editor, Xue, Guoliang, Advisory Editor, Ye, Yinyu, Advisory Editor, Blondin, Maude Josée, editor, Fernandes Trovão, João Pedro, editor, and Chaoui, Hicham, editor

Published
2022
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6. A MILP Model for Energy-Efficient Job Shop Scheduling Problem and Transport Resources

Author

Homayouni, S. Mahdi, Fontes, Dalila B. M. M., Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Tröltzsch, Fredi, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Reis, Ricardo, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Dolgui, Alexandre, editor, Bernard, Alain, editor, Lemoine, David, editor, von Cieminski, Gregor, editor, and Romero, David, editor

Published
2021
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21. A Biased Random Key Genetic Algorithm Approach for Unit Commitment Problem

Author

Roque, Luís A. C., Fontes, Dalila B. M. M., Fontes, Fernando A. C. C., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Pardalos, Panos M., editor, and Rebennack, Steffen, editor

Published
2011
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26. Model Predictive Control of Vehicle Formations

Author

Fontes, Fernando A. C. C., Fontes, Dalila B. M. M., Caldeira, Amélia C. D., Morari, Manfred, editor, Thoma, Manfred, editor, Hirsch, Michael J., editor, Commander, Clayton W., editor, Pardalos, Panos M., editor, and Murphey, Robert, editor

Published
2009
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34. A multistart biased random key genetic algorithm for the flexible job shop scheduling problem with transportation.

Author

Homayouni, S. Mahdi, Fontes, Dalila B. M. M., and Gonçalves, José F.

Subjects
PRODUCTION scheduling, GENETIC algorithms, TRANSPORTATION schedules, MODULAR construction, NP-hard problems
Abstract

This work addresses the flexible job shop scheduling problem with transportation (FJSPT), which can be seen as an extension of both the flexible job shop scheduling problem (FJSP) and the job shop scheduling problem with transportation (JSPT). Regarding the former case, the FJSPT additionally considers that the jobs need to be transported to the machines on which they are processed on, while in the latter, the specific machine processing each operation also needs to be decided. The FJSPT is NP-hard since it extends NP-hard problems. Good-quality solutions are efficiently found by an operation-based multistart biased random key genetic algorithm (BRKGA) coupled with greedy heuristics to select the machine processing each operation and the vehicles transporting the jobs to operations. The proposed approach outperforms state-of-the-art solution approaches since it finds very good quality solutions in a short time. Such solutions are optimal for most problem instances. In addition, the approach is robust, which is a very important characteristic in practical applications. Finally, due to its modular structure, the multistart BRKGA can be easily adapted to solve other similar scheduling problems, as shown in the computational experiments reported in this paper. [ABSTRACT FROM AUTHOR]

Published
2023
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49. A Decision Support System for self-promotion planning at a TV station

Author

Fontes, Dalila B. M. M., Pereira, P. A., Fontes, Fernando A. C. C., Faculdade de Engenharia, and Faculdade de Economia

Abstract

This paper describes a Decision Support System (DSS) to plan and maintain the best assignment of the weekly self-promotion space for a TV station. The DSS allows the decision makers to generate, evaluate, and compare different solutions, as well as include additional knowledge by changing manually the solutions provided. The DSS comprises an input data base, a statistic module, a heuristic tool, and a graphical interface. The information used is real data provided by a Portuguese TV station and by a company that provides daily audience information based on the audience of previous days. The heuristic comprises two steps. Firstly, feasible solutions are provided by a greedy constructive heuristic, which are then improved by a genetic algorithm optimizer. Finally, the best solution found is presented as a grid of spots-breaks allocation, that is the spots to be broadcasted in each break for each day of the week. The interface can also be used to manually change the current solution, if desirable. The changed solution is then evaluated. The self-promotion plan comprises the allocation of the several self-promotion spots to the different time slots of the self-promotion breaks for the following seven days. However, the audience information is received daily, which permits to replan previous allocations for the next seven days in a receding horizon control strategy.

Published
2019

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