PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2020 | 11 | nr 4 | 138--148
Tytuł artykułu

A Genetic Algorithm and B&B Algorithm for Integrated Production Scheduling, Preventive and Corrective Maintenance to Save Energy

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The rapid global economic development of the world economy depends on the availability of substantial energy and resources, which is why in recent years a large share of non-renewable energy resources has attracted interest in energy control. In addition, inappropriate use of energy resources raises the serious problem of inadequate emissions of greenhouse effect gases, with major impact on the environment and climate. On the other hand, it is important to ensure efficient energy consumption in order to stimulate economic development and preserve the environment. As scheduling conflicts in the different workshops are closely associated with energy consumption. However, we find in the literature only a brief work strictly focused on two directions of research: the scheduling with PM and the scheduling with energy. Moreover, our objective is to combine both aspects and directions of in-depth research in a single machine. In this context, this article addresses the problem of integrated scheduling of production, preventive maintenance (PM) and corrective maintenance (CM) jobs in a single machine. The objective of this article is to minimize total energy consumption under the constraints of system robustness and stability. A common model for the integration of preventive maintenance (PM) in production scheduling is proposed, where the sequence of production tasks, as well as the preventive maintenance (PM) periods and the expected times for completion of the tasks are established simultaneously; this makes the theory put into practice more efficient. On the basis of the exact Branch and Bound method integrated on the CPLEX solver and the genetic algorithm (GA) solved in the Python software, the performance of the proposed integer binary mixed programming model is tested and evaluated. Indeed, after numerically experimenting with various parameters of the problem, the B&B algorithm works relatively satisfactorily and provides accurate results compared to the GA algorithm. A comparative study of the results proved that the model developed was sufficiently efficient. (original abstract)
Rocznik
Tom
11
Numer
Strony
138--148
Opis fizyczny
Twórcy
autor
  • Sidi Mohammed Ben Abdellah University, Morocco; ECAM-EPMI, France
  • ECAM-EPMI, France
  • Sidi Mohammed Ben Abdellah University, Morocco
  • ECAM-EPMI, France
  • Sidi Mohammed Ben Abdellah University, Morocco
Bibliografia
  • EIA, 2013, International Energy Outlook 2013 (online), www.eia.gov/forecasts/ieo/pdf/0484(2013).pdf, accessed on 5 May 2018.
  • CSY, 2016, China Statistical Yearbook 2015 (online), www.stats.gov.cn/tjsj/ndsj/2016/indexeh.htm, accessed on 5 May 2018.
  • Wang S., Wang X., Yu J., Ma S., Liu M., Biobjective identical parallel machine scheduling to minimize total energy consumption and makespan, Journal of Cleaner Production (2018), doi: 10.1016/j.jclepro.2018.05.056.
  • Ding J., Song S., Zhang R., Chiong R., Wu C., Parallel machine scheduling under time-of-use electricity prices: new models and optimization approaches, IEEE Transactions on Automation Science and Engineering, 13, 2, 1138-1154, 2016.
  • Mouzon G., Operational methods and models for minimisation of energy consumption in a manufacturing environment, Ph.D. thesis, Wichita State University, Wichita, the United States of America, 2008.
  • Luo H., Du B., Huang G., Chen H., Li X., Hybrid flow shop scheduling considering machine electricity consumption cost, International Journal of Production Economics, 146, 423-439, 2013.
  • Liu Y., Dong H., Lohse N., Petrovic S., Gindy N., An investigation into minimizing total energy consumption and total weighted tardiness in job shops, Journal of Cleaner Production, 65, 87-96, 2014.
  • Gahm C., Denz F., Dirr M., Tuma A., Energy - efficient scheduling in manufacturing companies: a review and research framework, European Journal of Operational Research, 248, 3, 744-757, 2016.
  • Giret A., Trentesaux D., Prabhu V., Sustainability in manufacturing operations scheduling: a state of the art review, Journal of Manufacturing Systems, 37, 1, 126-140, 2015.
  • Merkert L., Harjunkoski I., Isaksson A., Saynevirta S., Saarela A., Sand G., Scheduling and energyindustrial challenges and opportunities, Computers and Chemical Engineering, 72, 183-198, 2015.
  • Sadiqi A. et al., Joint scheduling of jobs and variable maintenance activities in the flowshop sequencing problems: review, classification and opportunities, International Journal of Engineering Research in Africa, 39, 170-190, 2018.
  • Sadiqi A., El Abbassi I., El Barkany A., El Biyaali A., Comparative analysis the simultaneous scheduling problems of production and maintenance activities, April 2018 Indexed SCOPUS, IEEE Xplore, 10.1109. LOGISTIQUA.2018.8428283.
  • Zhiqiang Lu, Weiwei Cui, Xiaole Han, Integrated production and preventive maintenance scheduling for a single machine with failure uncertainty, Computers & Industrial Engineering, 80, 236-244, 2015.
  • Goren S., Sabuncuoglu I., Robustness and stability measures for scheduling single-machine environment, IIE Transactions, 40, 66-83, 2008.
  • Weinstein L., Chung C.H., Integrating maintenance and production decisions in a hierarchical production planning environment, Computers & Operations Research, 26, 1059-1074, 1999.
  • Lin W., Yu D.Y. Zhang C., Liu X., Zhang S., Tian Y., Liu S., Xie Z., A multi objective teachinglearning- based optimization algorithm to scheduling in turning processes for minimizing makespan and carbon footprint, J. Clean. Prod., 101, 337-347, 2015.
  • Zhang H., Deng Z., Fu Y., Lv L., Yan C., A process parameters optimization method of multi-pass dry milling for high efficiency, low energy and low carbon emissions, J. Clean. Prod., 148, 174-184, 2017.
  • Meng L., Zhang C., Shao X., Ren Y., Ren C., Mathematical modelling and optimisation of energy conscious hybrid flow shop scheduling problem with unrelated parallel machines, Int. J. Prod. Res., 1-27, 2018.
  • Baker K.R., Keller B., Solving the single-machine sequencing problem using integer programming, Computers & Industrial Engineering, 59, 4, 730- 735, 2010.
  • Sadiqi A., El Abbassi I., El Barkany A., El Biyaali A., Non-permutation flow shop scheduling problems with unavailability constraints to Minimize Total Energy Consumption, April 2019, 10.1109/ICOA.2019.8727649.
  • Clausen J., Branch and bound algorithms - Principles and examples, Department of Computer Science, University of Copenhagen, 1-30, 1999.
  • Assia S., El Abbassi I., El Barkany A., Darcherif M., El Biyaali A., Green Scheduling of Jobs and Flexible Periods of Maintenance in a Two- Machine Flowshop to Minimize Makespan, a Measure of Service Level and Total Energy Consumption, Advances in Operations Research, 1-9, 2020, doi: 10.1155/2020/9732563.
  • Sadiqi A., El Abbassi I., El Barkany A., Darcherif M., El Biyaali A., Speed scaling technique integrated in scheduling of production and maintenance under energy constraints using genetic algorithms, E3S Web Conf. 170 01029, 2020, doi: 10.1051/e3sconf/202017001029.
  • Sadiqi A., El Abbassi I., El Barkany A., Darcherif M., El Biyaali A., Optimizing electricity costs during integrated scheduling of jobs and stochastic preventive maintenance under time-ofuse electricity tariffs, Management and Production Engineering Review, 10, 123-132, 2019, doi: 10.24425/mper.2019.131452.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171610307

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.