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Articles

Algorithms for a two-agent single machine scheduling problem to minimize weighted number of tardy jobs

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Pages 785-811 | Received 01 Apr 2020, Published online: 23 Nov 2020

References

  • Agnetis, A., Mirchandani, P. B., Pacciarelli, D., Pacifici, A., Agnetis, A., Pacciarelli, D., & Pacifici, A. (2004). Scheduling Problems with Two Competing Age, 52(2), 229–242.
  • Baker, K. R., & Smith, J. C. (2003). A multiple-criterion model for machine scheduling. Journal of Scheduling, 6(1), 7-16.
  • Boudjehem, D., & Boudjehem, B. (2017). Improved heterogeneous particle swarm optimization. Journal of Information and Optimization Sciences, 38(3-4), 481-499.
  • Cesaret, B., Oǧuz, C., & Sibel Salman, F. (2012). A tabu search algorithm for order acceptance and scheduling. Computers and Operations Research, 39(6), 1197–1205.
  • Cheng, T. C. E., Cheng, S. R., Wu, W. H., Hsu, P. H., & Wu, C. C. (2011). A two-agent single-machine scheduling problem with truncated sum-of-processing-times-based learning considerations. Computers and Industrial Engineering, 60(4), 534–541.
  • Cheng, T. C. E., Ng, C. T., & Yuan, J. J. (2006). Multi-agent scheduling on a single machine to minimize total weighted number of tardy jobs. Theoretical Computer Science, 362(1–3), 273-281.
  • Cordeau, J. F., Laporte, G., & Mercier, A. (2001). A unified tabu search heuristic for vehicle routing problems with time windows. Journal of the Operational research society, 52(8), 928-936.
  • Glover, F. (1989). Tabu search—part I. ORSA Journal on computing, 1(3), 190-206.
  • González, M. A., Vela, C. R., González-Rodríguez, I., & Varela, R. (2013). Lateness minimization with Tabu search for job shop scheduling problem with sequence dependent setup times. Journal of Intelligent Manufacturing, 24(4), 741–754.
  • Graham, R. L., Lawler, E. L., Lenstra, J. K., & Kan, A. R. (1979). Optimization and approximation in deterministic sequencing and scheduling: a survey. In Annals of discrete mathematics (Vol. 5, pp. 287-326). Elsevier.
  • Karp, R. M. (1972). Reducibility among combinatorial problems. In Complexity of computer computations (pp. 85-103). Springer, Boston, MA.
  • Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. Neural Networks, 1995. Proceedings., IEEE International Conference on, 4, 1942–1948 vol.4.
  • Liao, C. J., Tseng, C. T., & Luarn, P. (2007). A discrete version of particle swarm optimization for flowshop scheduling problems. Computers & Operations Research, 34(10), 3099-3111.
  • Li, H., & Gajpal, Y. (2017). Two agents single machine scheduling problem with total completion time and total weighted completion time objectives. Operational Research and Management Science Letters, 1(1), 8-16.
  • Li, H., Gajpal, Y., & Bector, C. R. (2018). Single machine scheduling with two-agent for total weighted completion time objectives. Applied Soft Computing, 70, 147-156.
  • Li. H., Gajpal Y., and C.R. Bector (2020) A Survey of Single-Machine with Two-Agent Scheduling Problem with Due Date, “Journal of Industrial and Management Optimization”, 16 (3), 1329-1347
  • Li, X., & Gao, L. (2016). An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem. International Journal of Production Economics, 174, 93–110.
  • Meeran, S., & Morshed, M. S. (2012). A hybrid genetic tabu search algorithm for solving job shop scheduling problems: A case study. Journal of Intelligent Manufacturing, 23(4), 1063–1078.
  • M’Hallah, R., & Bulfin, R. L. (2003). Minimizing the weighted number of tardy jobs on a single machine. European Journal of Operational Research, 145(1), 45-56.
  • Moore, J. M. (1968). An n job, one machine sequencing algorithm for minimizing the number of late jobs. Management science, 15(1), 102-109.
  • Mor, B., & Mosheiov, G. (2010). Scheduling problems with two competing agents to minimize minmax and minsum earliness measures. European Journal of Operational Research, 206(3), 540–546.
  • Ng, C. T., Cheng, T. C. E., & Yuan, J. J. (2006). A note on the complexity of the problem of two-agent scheduling on a single machine. Journal of Combinatorial Optimization, 12(4), 387–394.
  • Pandey, S., Wu, L., Guru, S. M., & Buyya, R. (2010). A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments. 2010 24th IEEE International Conference on Advanced Information Networking and Applications, 400–407.
  • Perez-Gonzalez, P., & Framinan, J. M. (2014). A common framework and taxonomy for multicriteria scheduling problems with interfering and competing jobs: Multi-agent scheduling problems. European Journal of Operational Research, 235(1), 1–16.
  • Sahu, S. N., Gajpal, Y., & Debbarma, S. (2017). Two-agent-based single-machine scheduling with switchover time to minimize total weighted completion time and makespan objectives. Annals of Operations Research, 1-18.
  • Schultz, D., Oh, S. H., Grecas, C. F., Albani, M., Sanchez, J., Arbib, C., … & Lombardi, G. (2002, June). A QoS concept for packet oriented S-UMTS services. In IST Mobile and Wireless Telecommunications Summit.
  • Shahvari, O., Salmasi, N., Logendran, R., & Abbasi, B. (2012). An efficient tabu search algorithm for flexible flow shop sequence-dependent group scheduling problems. International Journal of Production Research, 50(15), 4237–4254.
  • Tasgetiren, M. F., Sevkli, M., Liang, Y. C., & Gencyilmaz, G. (2004, September). Particle swarm optimization algorithm for permutation flowshop sequencing problem. International Workshop on Ant Colony Optimization and Swarm Intelligence (pp. 382-389). Springer, Berlin, Heidelberg.
  • Wang, J. Q., Fan, G. Q., Zhang, Y., Zhang, C. W., & Leung, J. Y. T. (2017). Two-agent scheduling on a single parallel-batching machine with equal processing time and non-identical job sizes. European Journal of Operational Research, 258(2), 478-490.
  • W. H. Wu. (2013). An exact and meta-heuristic approach for two-agent single-machine scheduling problem. Journal of Marine Science and Technology (Taiwan), 21(2), 215–221.
  • Wu, W. H., Yin, Y., Cheng, T. C. E., Lin, W. C., Chen, J. C., Luo, S. Y., & Wu, C. C. (2017). A combined approach for two-agent scheduling with sum-of-processing-times-based learning effect. Journal of the Operational Research Society, 68(2), 111–120.
  • Xingong, Z., & Yong, W. (2017). Two-agent scheduling problems on a single-machine to minimize the total weighted late work. Journal of Combinatorial optimization, 33(3), 945-955.
  • Yin, Y., Cheng, T. C. E., & Wang, D. (2020). Due date-related scheduling with two agents: models and algorithms. Springer.
  • Yoshida, H., Kawata, K., Fukuyama, Y., Takayama, S., & Nakanishi, Y. (2000). A Particle swarm optimization for reactive power and voltage control considering voltage security assessment. IEEE Transactions on Power Systems, 15(4), 1232–1239.
  • Yu, C., Semeraro, Q., & Matta, A. (2018). A genetic algorithm for the hybrid flow shop scheduling with unrelated machines and machine eligibility. Computers & Operations Research, 100, 211-229.

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