Synchronizing heterogeneous processes remains a difficult issue in Scheduling area. Related ILP models are in trouble, because of large gaps induced by rational relaxation. We choose here to deal with it while emulating the interactions which take place between the various players of such heterogeneous processes, and propose a pipe-line decomposition of a dynamic programming process designed in order to schedule energy production and energy consumption
Keywords: Scheduling, dynamic programming, energy management
@article{RO_2021__55_4_2359_0,
author = {Bendali, Fatiha and Mole Kamga, Eloise and Mailfert, Jean and Quilliot, Alain and Toussaint, H\'el\`ene},
title = {Pipe-lining dynamic programming processes to synchronize both the production and the consumption of energy},
journal = {RAIRO. Operations Research},
pages = {2359--2383},
year = {2021},
publisher = {EDP-Sciences},
volume = {55},
number = {4},
doi = {10.1051/ro/2021094},
mrnumber = {4296610},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ro/2021094/}
}
TY - JOUR AU - Bendali, Fatiha AU - Mole Kamga, Eloise AU - Mailfert, Jean AU - Quilliot, Alain AU - Toussaint, Hélène TI - Pipe-lining dynamic programming processes to synchronize both the production and the consumption of energy JO - RAIRO. Operations Research PY - 2021 SP - 2359 EP - 2383 VL - 55 IS - 4 PB - EDP-Sciences UR - https://www.numdam.org/articles/10.1051/ro/2021094/ DO - 10.1051/ro/2021094 LA - en ID - RO_2021__55_4_2359_0 ER -
%0 Journal Article %A Bendali, Fatiha %A Mole Kamga, Eloise %A Mailfert, Jean %A Quilliot, Alain %A Toussaint, Hélène %T Pipe-lining dynamic programming processes to synchronize both the production and the consumption of energy %J RAIRO. Operations Research %D 2021 %P 2359-2383 %V 55 %N 4 %I EDP-Sciences %U https://www.numdam.org/articles/10.1051/ro/2021094/ %R 10.1051/ro/2021094 %G en %F RO_2021__55_4_2359_0
Bendali, Fatiha; Mole Kamga, Eloise; Mailfert, Jean; Quilliot, Alain; Toussaint, Hélène. Pipe-lining dynamic programming processes to synchronize both the production and the consumption of energy. RAIRO. Operations Research, Tome 55 (2021) no. 4, pp. 2359-2383. doi: 10.1051/ro/2021094
[1] , Energy-efficient algorithms. Commun. ACM 53 (2010) 86–96. | DOI
[2] , and , Low complexity scheduling algorithms minimizing the energy for tasks with agreeable deadlines. Discrete Appl. Math. 175 (2014) 1–10. | MR | Zbl | DOI
[3] , Scheduing unit tasks to minimize the number of idle periods: a polynomial time algorithm for offline dynamic power management. In: Proc. 17 th Annual ACM-SIMA Symposium on Discrete Algorithms (2006) 364–367. | MR | Zbl
[4] , and , Modèles et Algorithmes en Ordonnancement. Ed Ellipses (2004) 198–203.
[5] , and , A survey of design techniques for system level dynamic power management. IEEE Trans. Very Large Scale Integr. Syst. 8 (2000) 299–316. | DOI
[6] and , Systematic literature review of decision support models for energy efficient decision planning. Comput. Ind. Eng. 101 (2016) 243–259. | DOI
[7] , Batteries and ultracapacitors for electric, hybrid, and fuel cell vehicles. Proc. IEEE 95 (2007) 806–820. | DOI
[8] , The state of the art of electric, hybrid, and fuel cell vehicles. Proc. IEEE 95 (2007) 704–718. | DOI
[9] and , Homogeneous non idling schedules of unit-time jobs on identical parallel machines. Discrete Appl. Math. 161 (2013) 1586–1597. | MR | Zbl | DOI
[10] and , A polynomial algorithm for the homogeneous non idling scheduling problem of unit-time independent jobs on identical parallel machines. Discrete Appl. Math. 243 (2018) 132–139. | MR | DOI
[11] , and , Anchored reactive and proactive solutions to the CPM-scheduling problem. Eur. J. Oper. Res. 261 (2017) 67–74. | MR | DOI
[12] , and , Scheduling to minimize gaps and power consumption. SPAA (2007) 46–54.
[13] , Synchronization in vehicle routing: a survey of VRPs with multiple synchronization constraints. Transp. Sci. 46 (2012) 297–316. | DOI
[14] , , , , , , and , Toward energy and resource efficient manufacturing: a process and system approach. CIRP Ann. – Manuf. Technol. 61 (2012) 587–609. | DOI
[15] and , A green vehicle routing problem. Transp. Res. Part E Logistics Transp. Rev. 109 (2012) 100–114. | DOI
[16] , , , , and , A metaheuristic for the time dependent pollution-routing problem. Eur. J. Oper. Res. 259 (2017) 972–991. | MR | DOI
[17] , and , Sustainability in manufacturing operations scheduling: a state of art review. J. Manuf. Syst. 37 (2015) 126–140. | DOI
[18] , and , Light, Water, Hydrogen: The Solargeneration of Hydrogen By Water Photoelectrolysis. Springer-Verlag US (2008). | DOI
[19] and , Algorithmic problems in power management. SIGACT News 36 (2003) 63–76. | DOI
[20] , and . Energy minimizing vehicle routing problem, edited by , and . In: Combinatorial Optimization and Applications, Berlin, Heidelberg (2007) 62–71. | MR | Zbl | DOI
[21] , , and , The electric vehicle routing problem with shared charging stations. Int. Trans. Oper. Res. 26 (2018) 1211–1243. | MR | DOI
[22] , Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem. Comput. Ind. Eng. 59 (2010) 157–165. | DOI
[23] , Energy consumption and cost-benefit analysis of hybrid and electric city buses. Transp. Res. Part C: Emerg. Technol. 38 (2014) 1–15. | DOI
[24] , Méthodes et outils pour l’ordonnancement d’ateliers avec prise en compte de contraintes additionnelles : énergétiques et environnementales. Thèse de Doctorat, Université Clermont-Auvergne, France (2017).
[25] , Thermochemical and Thermal/Photo Hybrid Solar Water Splitting. Springer, New York, New York, NY (2008).
[26] , , , and , Survey of green vehicle routing problem: past and future trends. Expert Syst. App. 41 (2014) 1118–1138. | DOI
[27] , , and , Simultaneous Management of Energy Production and Consumption. In: Proc. IEEE CODIT 2020 (2020) 8.
[28] , , and , Energy management in production: A novel method to develop key performance indicators for improving energy efficiency. Appl. Energy 149 (2015) 46–61. | DOI
[29] and , Smart production scheduling with time-dependent and machine-dependent electricity cost by considering distributed energy resources and energy storage. IJPR 52 (2013) 3922–3939. | DOI
[30] , and , Optimization of production scheduling with time-dependent and machine-dependent electricity cost for industrial energy efficiency. Int. J. Adv. Manuf. Technol. 68 (2013) 523–535. | DOI
[31] , , and , Production scheduling with a piecewise-linear energy cost function. In: 2016 IEEE Symposium Series on Computational Intelligence (SSCI). (2016) 1–8.
[32] and , Optimizing energy costs by intelligent production scheduling, edited by and . In: Glocalized Solutions for Sustainability in Manufacturing. Berlin, Heidelberg (2011) 293–298. | DOI
[33] , , and , Green vehicle routing and scheduling problem with split delivery. Joint, EURO/ALIO, International Conference 2018 on Applied Combinatorial Optimization, (EURO/ALIO 2018). Electron. Notes Discrete Math. 69 (2018) 13–20. | MR
[34] , , and , Efficient energy-optimal routing for electric vehicles. AAAI (2011).
[35] , and , The electric vehicle-routing problem with time windows and recharging stations. Transp. Sci. 48 (2014) 500–520. | DOI
[36] , , , , and , Plug-in hybrid electric vehicles and smart grid: micro simulation. Transp. Res. C 28 (2014) 74–86. | DOI
Cité par Sources :





