Open Access
RAIRO-Oper. Res.
Volume 56, Number 4, July-August 2022
Page(s) 2621 - 2649
Published online 18 August 2022
  • N.R. Adam and J. Surkis, Priority update intervals and anomalies in dynamic ratio type job shop scheduling rules. Manage. Sci. 26 (1980) 1227–1237. [CrossRef] [Google Scholar]
  • M.M. Ahmadian and A. Salehipour, The just-in-time job shop scheduling problem with distinct due-dates for operations. J. Heuristics 27 (2021) 175–204. [CrossRef] [Google Scholar]
  • M.M. Ahmadian, A. Salehipour and T.C.E. Cheng, A meta-heuristic to solve the just-in-time job-shop scheduling problem. Eur. J. Oper. Res. 288 (2021) 14–29. [CrossRef] [Google Scholar]
  • R.P. Araujo, A.G. dos Santos and J.E.C. Arroyo, Genetic Algorithm and Local Search for Just-in-Time Job-Shop Scheduling. In: Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC 2009) (2009) 955–961. [Google Scholar]
  • P. Baptiste, M. Flamini and F. Sourd, Lagrangian bounds for just-in-time job-shop scheduling. Comput. Oper. Res. 35 (2008) 906–915. [CrossRef] [MathSciNet] [Google Scholar]
  • J. Bauman and J. Józefowska, Minimizing the earliness–tardiness costs on a single machine. Comput. Oper. Res. 33 (2006) 3219–3230. [CrossRef] [Google Scholar]
  • J.C. Beck and P. Refalo, A hybrid approach to scheduling with earliness and tardiness costs. Ann. Oper. Res. 118 (2003) 49–71. [CrossRef] [MathSciNet] [Google Scholar]
  • J.H. Blackstone, D.T. Phillips and G.L. Hogg, A state-of-the-art survey of dispatching rules for manufacturing job shop operations. Int. J. Prod. Res. 20 (1982) 27–45. [CrossRef] [Google Scholar]
  • F.D. Croce and M. Trubian, Optimal idle time insertion in early-tardy parallel machines scheduling with precedence constraints. Prod. Plan. Control. 13 (2002) 133–142. [CrossRef] [Google Scholar]
  • P. Chretienne, Minimizing the earliness and tardiness cost of a sequence of tasks on a single machine. RAIRO-Oper. Res. 35 (2001) 165–187. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • P. Chretienne and F. Sourd, PERT scheduling with convex cost functions. Theor. Comput. Sci. 292 (2003) 145–164. [CrossRef] [Google Scholar]
  • T. Cleveland, Number Theory. Ed-Tech Press (2020). [Google Scholar]
  • E. Danna, E. Rothberg and C.L. Pape, Integrating mixed integer programming and local search: A case on Job-shop scheduling problems. In: Proceedings of the Fifth International Workshop on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimisation Problems (CPAIOR’03) (2003) 65–79. [Google Scholar]
  • A.G. dos Santos, R.P. Araujo and J.E.C. Arroyo, A combination of evolutionary algorithm, mathematical programming, and a new local search procedure for the just-in-time job-shop scheduling problem. In: Vol. 6073 of Learning and Intelligent Optimization (LION 2010), edited by C. Blum and R. Battiti, Lecture Notes in Computer Science, Springer-Verlag, Berlin- Heidelberg (2010) 10–24. [CrossRef] [Google Scholar]
  • G. Feng and H.C. Lau, Efficient algorithms for machine scheduling problems with earliness and tardiness penalties. Ann. Oper. Res. 159 (2008) 83–95. [CrossRef] [MathSciNet] [Google Scholar]
  • M.R. Garey, R.E. Tarjan and G.T. Wilfong, One-Processor Scheduling with Symmetric Earliness and Tardiness Penalties. Math. Oper. Res. 13 (1988) 330–348. [CrossRef] [MathSciNet] [Google Scholar]
  • B. Giffler and G.L. Thompson, Algorithms for solving production-scheduling problems. Oper. Res. 8 (1960) 487–503. [CrossRef] [Google Scholar]
  • B.S. Girish, An efficient hybrid particle swarm optimization algorithm in a rolling horizon framework for the aircraft landing problem. Appl. Soft Comput. 44 (2016) 200–221. [CrossRef] [Google Scholar]
  • Y. Hendel and F. Sourd, An improved earliness–tardiness timing algorithm. Comput. Oper. Res. 34 (2007) 2931–2938. [CrossRef] [Google Scholar]
  • IBM software, IBM ILOG CPLEX Optimization Studio CPLEX User’s Manual version 12 Release 8, IBM, 2017. Available online: [Google Scholar]
  • A.S. Jain and S. Meeran, Deterministic job-shop scheduling: Past, present and future. Eur. J. Oper. Res. 113 (1999) 390–434. [CrossRef] [Google Scholar]
  • J. Józefowska, Just-in-time concept in manufacturing and computer systems, In: Just-In-Time Scheduling: Models and Algorithms for Computer and Manufacturing Systems, Vol. 106 of International Series In Operations Research,Springer, Boston (2007) 1–23. [Google Scholar]
  • J. Kelbel and Z. Hanzalek, Solving production scheduling with earliness/tardiness penalties by constraint programming. J. Intell. Manuf. 22 (2011) 553–562. [CrossRef] [Google Scholar]
  • C.Y. Lee and J.Y. Choi, A genetic algorithm for job sequencing problems with distinct due dates and general early-tardy penalty weights. Comput. Oper. Res. 22 (1995) 857–869. [CrossRef] [Google Scholar]
  • J. Monette, Y. Deville and P.V. Hentenryck, Just-in-time scheduling with constraint programming. In: Proceedings of the Nineteenth International Conference on Automated Planning and Scheduling (ICAPS 2009) (2009) 241–248. [Google Scholar]
  • S.G. Ponnambalam, N. Jawahar and B.S. Girish, Giffler and Thompson procedure based genetic algorithms for scheduling job shops, In: Computational intelligence of flow shop and job shop scheduling, In Vol. 230 of Studies in Computational Intelligence, Springer-Verlag, Berlin-Heidelberg (2010) 229–259. [Google Scholar]
  • W. Szwarc and S.K. Mukhopadhyay, Optimal timing schedules in earliness-tardiness single machine sequencing. Nav. Res. Logist. 42 (1995) 1109–1114. [CrossRef] [Google Scholar]
  • M. Vanhoucke, E. Demeulemeester and W. Herroelen, An exact procedure for the resource-constrained weighted earliness–Tardiness project scheduling problem. Ann. Oper. Res. 102 (2001) 179–196. [CrossRef] [MathSciNet] [Google Scholar]
  • G. Wan and B.P.C. Yen, Tabu search for single machine scheduling with distinct due windows and weighted earliness/tardiness penalties. Eur. J. Oper. Res. 142 (2002) 271–281. [CrossRef] [Google Scholar]
  • S. Wang and Y. Li, Variable neighbourhood search and mathematical programming for just-in-time job-shop scheduling problem. Math. Probl. Eng. 2014 (2014) 1–9. [Google Scholar]
  • H. Yang, J. Li and L. Qi, An Improved Genetic Algorithm For Just-In-Time Job-Shop Scheduling Problem. Adv. Mat. Res. 472–475 (2012) 2462–2467. [Google Scholar]
  • H. Yang, Q. Sun, C. Saygin and S. Sun, Job shop scheduling based on earliness and tardiness penalties with due dates and deadlines: an enhanced genetic algorithm. Int. J. Adv. Manuf. Technol. 61 (2012) 657–666. [CrossRef] [Google Scholar]
  • J. Zhang, G. Ding, Y. Zhou, S. Qin and J. Fu, Review of job shop scheduling research and its new perspectives under industry 4.0. J. Intell. Manuf. 30 (2019) 1809–1830. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.