EDP Sciences logo
Subscriber Authentication Point
Search
Menu
All issues Volume 57 / No 3 (May-June 2023) RAIRO-Oper. Res., 57 3 (2023) 1453-1479 References
Open Access
Issue
RAIRO-Oper. Res.
Volume 57, Number 3, May-June 2023
Page(s) 1453 - 1479
DOI https://doi.org/10.1051/ro/2023050
Published online 21 June 2023
  • A. Abbasi-Pooya and A. Husseinzadeh Kashan, New mathematical models and a hybrid grouping evolution strategy algorithm for optimal helicopter routing and crew pickup and delivery. Comput. Ind. Eng. 112 (2017) 35–56. [CrossRef] [Google Scholar]
  • M. Al-Salamah, Constrained binary artificial bee colony to minimize the makespan for single machine batch processing with non-identical job sizes. Appl. Soft Comput. 29 (2015) 379–385. [CrossRef] [Google Scholar]
  • Y. Bartal, S. Leonardi, A. Marchetti-Spaccamela, J. Sgall and L. Stougie, Multiprocessor scheduling with rejection. SIAM J. Discrete Math. 13 (2000) 64–78. [CrossRef] [MathSciNet] [Google Scholar]
  • J.C. Bean, Genetic algorithms and random keys for sequencing and optimization. ORSA J. Comput. 6 (1994) 154–160. [Google Scholar]
  • Z. Cao and X. Yang, A PTAS for parallel batch scheduling with rejection and dynamic job arrivals. Theor. Comput. Sci. 410 (2009) 2732–2745. [CrossRef] [Google Scholar]
  • D.W. Engels, D.R. Karger, S.G. Kolliopoulos, S. Sengupta, R. Uma and J. Wein, Techniques for scheduling with rejection. J. Algorithms 49 (2003) 175–191. [CrossRef] [MathSciNet] [Google Scholar]
  • E. Falkenauer, A new representation and operators for genetic algorithms applied to grouping problems. Evol. Comput. 2 (1994) 123–144. [CrossRef] [Google Scholar]
  • F.J. Ghazvini and L. Dupont, Minimizing mean flow times criteria on a single batch processing machine with non-identical jobs sizes. Int. J. Prod. Econ. 55 (1998) 273–280. [CrossRef] [Google Scholar]
  • C. He, J.Y.-T. Leung, K. Lee and M.L. Pinedo, Scheduling a single machine with parallel batching to minimize makespan and total rejection cost. Discrete Appl. Math. 204 (2016) 150–163. [CrossRef] [MathSciNet] [Google Scholar]
  • A. Husseinzadeh Kashan, League championship algorithm: a new algorithm for numerical function optimization. in 2009 International Conference of Soft Computing and Pattern Recognition (2009) 43–48. [Google Scholar]
  • A. Husseinzadeh Kashan, League Championship Algorithm (LCA): an algorithm for global optimization inspired by sport championships. Appl. Soft Comput. 16 (2014) 171–200. [CrossRef] [Google Scholar]
  • A. Husseinzadeh Kashan and B. Karimi, An improved mixed integer linear formulation and lower bounds for minimizing makespan on a flow shop with batch processing machines. Int. J. Adv. Manuf. Syst. 40 (2009) 582. [CrossRef] [Google Scholar]
  • A. Husseinzadeh Kashan, B. Karimi and F. Jolai, Effective hybrid genetic algorithm for minimizing makespan on a single-batch-processing machine with non-identical job sizes. Int. J. Prod. Res. 44 (2006) 2337–2360. [CrossRef] [Google Scholar]
  • A. Husseinzadeh Kashan, M. Husseinzadeh Kashan and S. Karimiyan, A particle swarm optimizer for grouping problems. Inf. Sci. 252 (2013) 81–95. [CrossRef] [Google Scholar]
  • A. Husseinzadeh Kashan, B. Karimi and A. Noktehdan, A novel discrete particle swarm optimization algorithm for the manufacturing cell formation problem. Int. J. Adv. Manuf. Syst. 73 (2014) 1543–1556. [CrossRef] [Google Scholar]
  • A. Husseinzadeh Kashan, A.A. Akbari and B. Ostadi, Grouping evolution strategies: an effective approach for grouping problems. Appl. Math. Model. 39 (2015) 2703–2720. [CrossRef] [MathSciNet] [Google Scholar]
  • A. Husseinzadeh Kashan, S. Jalili and S. Karimiyan, Optimum structural design with discrete variables using league championship algorithm. Civil Eng. Infrastruct. J. 51 (2018) 253–275. [Google Scholar]
  • A. Husseinzadeh Kashan, R. Tavakkoli Moghaddam and M. Gen, Find-Fix-Finish-Exploit-Analyze (F3EA) meta-heuristic algorithm: an effective algorithm with new evolutionary operators for global optimization. Comput. Ind. Eng. 128 (2019) 92–218. [Google Scholar]
  • Z.-H. Jia, M.-L. Pei and J.Y.-T. Leung, Multi-objective ACO algorithms to minimise the makespan and the total rejection cost on BPMs with arbitrary job weights. Int. J. Syst. Sci. 48 (2017) 3542–3557. [CrossRef] [Google Scholar]
  • Z.-H. Jia, S.-Y. Huo, K. Li and H.-P. Chen, Integrated scheduling on parallel batch processing machines with non-identical capacities. Eng. Optim. (2019). [Google Scholar]
  • M. Jin, X. Liu and W. Luo, Single-machine parallel-batch scheduling with nonidentical job sizes and rejection. Mathematics 8 (2020) 258. [CrossRef] [Google Scholar]
  • M. Kong, X. Liu, J. Pei, Z. Zhou and P.M. Pardalos, Parallel-batching scheduling of deteriorating jobs with non-identical sizes and rejection on a single machine. Optim. Lett. 14 (2020) 857–871. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Li, G. Li, X. Wang and Q. Liu, Minimizing makespan on a single batching machine with release times and non-identical job sizes. Oper. Res. Lett. 33 (2005) 157–164. [CrossRef] [MathSciNet] [Google Scholar]
  • L. Lu, L. Zhang and J. Yuan, The unbounded parallel batch machine scheduling with release dates and rejection to minimize makespan. Theor. Comput. Sci. 396 (2008) 283–289. [CrossRef] [Google Scholar]
  • L. Lu, T.E. Cheng, J. Yuan and L. Zhang, Bounded single-machine parallel-batch scheduling with release dates and rejection. Comput. Oper. Res. 36 (2009) 2748–2751. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Lu, H. Feng and X. Li, Minimizing the makespan on a single parallel batching machine. Theor. Comput. Sci. 411 (2010) 1140–1145. [CrossRef] [Google Scholar]
  • S. Melouk, P. Damodaran and P.-Y. Chang, Minimizing makespan for single machine batch processing with non-identical job sizes using simulated annealing. Int. J. Prod. Econ. 87 (2004) 141–147. [CrossRef] [Google Scholar]
  • J. Ou, Near-linear-time approximation algorithms for scheduling a batch-processing machine with setups and job rejection. J. Sched. 23 (2020) 525–538. [CrossRef] [MathSciNet] [Google Scholar]
  • N.R. Parsa, B. Karimi and A. Husseinzadeh Kashan, A branch and price algorithm to minimize makespan on a single batch processing machine with non-identical job sizes. Comput. Oper. Res. 37 (2010) 1720–1730. [CrossRef] [MathSciNet] [Google Scholar]
  • N.R. Parsa, B. Karimi and S.M. Husseini, Minimizing total flow time on a batch processing machine using a hybrid max–min ant system. CAIE 99 (2016) 372–381. [Google Scholar]
  • C.N. Potts and M.Y. Kovalyov, Scheduling with batching: a review. Eur. J. Oper. Res. 120 (2000) 228–249. [CrossRef] [Google Scholar]
  • D. Shabtay, The single machine serial batch scheduling problem with rejection to minimize total completion time and total rejection cost. Eur. J. Oper. Res. 233 (2014) 64–74. [CrossRef] [Google Scholar]
  • R. Uzsoy, Scheduling a single batch processing machine with non-identical job sizes. Int. J. Prod. Res. 32 (1994) 1615–1635. [Google Scholar]
  • C.-S. Wang and R. Uzsoy, A genetic algorithm to minimize maximum lateness on a batch processing machine. Comput. Oper. Res. 29 (2002) 1621–1640. [CrossRef] [MathSciNet] [Google Scholar]
  • R. Xu, H. Chen and X. Li, Makespan minimization on single batch-processing machine via ant colony optimization. Comput. Oper. Res. 39 (2012) 582–593. [CrossRef] [MathSciNet] [Google Scholar]
  • Y. Yin, T.C.E. Cheng, D. Wang and C.-C. Wu, Improved algorithms for single-machine serial-batch scheduling with rejection to minimize total completion time and total rejection cost. IEEE Trans. Syst. Man Cybern. Syst. 46 (2016) 1578–1588. [CrossRef] [Google Scholar]
  • L. Zhang, L. Lu and J. Yuan, Single machine scheduling with release dates and rejection. Eur. J. Oper. Res. 198 (2009) 975–978. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Zhou, J. Xie, N. Du and Y. Pang, A random-keys genetic algorithm for scheduling unrelated parallel batch processing machines with different capacities and arbitrary job sizes. Appl. Math. 334 (2018) 254–268. [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.