A time-dependent scheduling problem to minimize the sum of the total weighted tardiness among two agents

Wen-Hung Wu; Yunqiang Yin; Wen-Hsiang Wu; Chin-Chia Wu; Peng-Hsiang Hsu

doi:10.3934/jimo.2014.10.591

Previous Article
The inverse parallel machine scheduling problem with minimum total completion time
JIMO Home
This Issue
Next Article
Multimodal image registration by elastic matching of edge sketches via optimal control

April 2014, 10(2): 591-611. doi: 10.3934/jimo.2014.10.591

A time-dependent scheduling problem to minimize the sum of the total weighted tardiness among two agents

Wen-Hung Wu ^1, , Yunqiang Yin ^2, , Wen-Hsiang Wu ^3, , Chin-Chia Wu ^4, and Peng-Hsiang Hsu ^1,

1.	Department of Business Administration, Kang-Ning Junior College of Medical Care and Management, Taipei, Taiwan, Taiwan
2.	College of Sciences, East China Institute of Technology, Fuzhou, Jiangxi 344000, China
3.	Department of Healthcare Management, Yuanpei University, Hsinchu, Taiwan
4.	Department of Statistics, Feng Chia University, Taichung, Taiwan

Received September 2012 Revised April 2013 Published October 2013

Abstract
Related Papers

The problem of scheduling with time-dependent processing times has been studied for more than two decades and significant advances have been made over the years. However, most work has paid more attention to the single-criterion models. Furthermore, most heuristics are constructed for the time-dependent scheduling problems in a step-by-step way. Motivated by the observations, this paper studies a two-agent scheduling model with increasing linear deterioration jobs in which the processing time of a job is modeled as an increasing linear function of its starting time. The objective function is to minimize the sum of the maximum weighted tardiness of the jobs of the first agent and the total weighted tardiness of the jobs of the second agent. This problem is known to be strongly NP-hard. Thus, as an alternative, the branch-and-bound, ant colony algorithm and simulated annealing algorithms are developed for the problem. Computational results are also presented to determine the performance of the proposed algorithms.

Keywords: ant colony algorithm, deterioration jobs., simulated annealing algorithm, Scheduling, two-agent.

Mathematics Subject Classification: Primary: 90B35; Secondary: 68M2.

Citation: Wen-Hung Wu, Yunqiang Yin, Wen-Hsiang Wu, Chin-Chia Wu, Peng-Hsiang Hsu. A time-dependent scheduling problem to minimize the sum of the total weighted tardiness among two agents. Journal of Industrial & Management Optimization, 2014, 10 (2) : 591-611. doi: 10.3934/jimo.2014.10.591

References:

[1]	A. Agnetis, P. B. Mirchandani, D. Pacciarelli and A. Pacifici, Scheduling problems with two competing agents, Operations Research, 52 (2004), 229-242. doi: 10.1287/opre.1030.0092. Google Scholar
[2]	A. Agnetis, D. Pacciarelli and A. Pacifici, Multi-agent single machine scheduling, Annals of Operations Research, 150 (2007), 3-15. doi: 10.1007/s10479-006-0164-y. Google Scholar
[3]	B. Alidaee and N. K. Womer, Scheduling with time dependent processing times: Review and extensions, Journal of the Operational Research Society, 50 (1999), 711-729. Google Scholar
[4]	A. Allahverdi and F. S. Al-Anzi, Using two-machine flowshop with maximum lateness objective to model multimedia data objects scheduling problem for WWW applications, Computers and Operations Research, 29 (2002), 971-994. doi: 10.1016/S0305-0548(00)00097-6. Google Scholar
[5]	A. Bachman and A. Janiak, Scheduling Jobs with Special Type of Start Time Dependent Processing Times, Report No 34/97, Institute of Engineering Cybernetics, Wroclaw University of Technology, 1997. Google Scholar
[6]	K. R. Baker and J. C. Smith, A multiple-criterion model for machine scheduling, Journal of Scheduling, 6 (2003), 7-16. doi: 10.1023/A:1022231419049. Google Scholar
[7]	D. Ben-Arieh and O. Maimon, Annealing method for PCB assembly scheduling on two sequential machines, International Journal of Computer Integrated Manufacturing, 5 (1992), 361-367. doi: 10.1080/09511929208944543. Google Scholar
[8]	S. Browne and U. Yechiali, Scheduling deteriorating jobs on a single processor, Operations Research, 38 (1990), 495-498. doi: 10.1287/opre.38.3.495. Google Scholar
[9]	S. R. Cheng, A single-machine two-agent scheduling problem by GA approach, Asia-Pacific Journal of Operational Research, 29 (2012), 1250013, 22 pp. doi: 10.1142/S0217595912500133. Google Scholar
[10]	T. C. E. Cheng, Q. Ding and B. M. T. Lin, A concise survey of scheduling with time-dependent processing times, European Journal of Operational Research, 152 (2004), 1-13. doi: 10.1016/S0377-2217(02)00909-8. Google Scholar
[11]	T. C. E. Cheng, C. T. Ng and J. J. Yuan, Multi-agent scheduling on a single machine to minimize total weighted number of tardy jobs, Theoretical Computer Science, 362 (2006), 273-281. doi: 10.1016/j.tcs.2006.07.011. Google Scholar
[12]	T. C. E. Cheng, C. T. Ng and J. J. Yuan, Multi-agent scheduling on a single machine with max-form criteria, European Journal of Operational Research, 188 (2008), 603-609. doi: 10.1016/j.ejor.2007.04.040. Google Scholar
[13]	T. C. E. Cheng, S. R. Cheng, W. H. Wu, P. H. Hsu and C. C. Wu, A two-agent single- machine scheduling problem with truncated sum-of-processing-times-based learning considerations, Computers & Industrial Engineering, 60 (2011), 534-541. doi: 10.1016/j.cie.2010.12.008. Google Scholar
[14]	T. C. E. Cheng, W. H. Wu, S. R. Cheng and C. C. Wu, Two-agent scheduling with position- based deteriorating jobs and learning effects, Applied Mathematics and Computation, 217 (2011), 8804-8824. doi: 10.1016/j.amc.2011.04.005. Google Scholar
[15]	T. C. E. Cheng, Y. H. Chung, S. C. Liao and W. C Lee, Two-agent singe-machine scheduling with release times to minimize the total weighted completion time, Computers & Operations Research, 40 (2013), 353-361. doi: 10.1016/j.cor.2012.07.013. Google Scholar
[16]	C. Chu, A branch-and-bound algorithm to minimize total tardiness with different release dates, Naval Research Logistics, 39 (1992), 859-875. Google Scholar
[17]	A. Colorni, M. Dorigo, M. Maniezzo, I. F. J. Varela and P. Bourgine, Distributed Optimization by Ant Colonies, Proceedings of the first European Conference on Artificial Life, Pairs, 1991. Google Scholar
[18]	A. Colorni, M. Dorigo, V. Maniezzo and M. Trubian, Ant system for job-shop scheduling, Belgian Journal of Operations Research, 34 (1994), 39-53. Google Scholar
[19]	M. Dorigo, Di Caro G and L. M. Gambardella, Ant algorithms for discrete optimization, Artificial Life, 5 (1999), 137-172. doi: 10.1162/106454699568728. Google Scholar
[20]	M. Dorigo and L. M. Gambardella, Ant colony system: A cooperative learning approach to travel salesman problem, IEEE Trans Evol Computing, 1 (1997), 53-66. doi: 10.1109/4235.585892. Google Scholar
[21]	M. L. Fisher, A dual algorithm for the one-machine scheduling problem,, Math Programming, 11 (): 229. doi: 10.1007/BF01580393. Google Scholar
[22]	R. L. Graham, E. L. Lawler, J. K. Lenstra and A. H. G. Rinnooy Kan, Optimization and heuristic in deterministic sequencing and scheduling: A survey, Annals of Discrete Mathematics, 5 (1979), 287-326. doi: 10.1016/S0167-5060(08)70356-X. Google Scholar
[23]	A. Janiak, T. Krysiak and R. Trela, Scheduling problems with learning and aging effects: A survey, Decision Making in Manufacturing and Services, 5 (2011), 19-36. Google Scholar
[24]	S. Kirkpatrick, C. Gelatt and M. Vecchi, Optimization by simulated annealing, Science, 220 (1983), 671-680. doi: 10.1126/science.220.4598.671. Google Scholar
[25]	A. S. Kunnathur and S. K. Gupta, Minimizing the makespan with late start penalties added to processing times in a single facility scheduling problem, European Journal of Operation Research, 47 (1990), 56-64. doi: 10.1016/0377-2217(90)90089-T. Google Scholar
[26]	K. Lee, B. C. Choi, J. Y. T. Leung and M. L. Pinedo, Approximation algorithms for multi-agent scheduling to minimize total weighted completion time, Information Processing Letters, 109 (2009), 913-917. doi: 10.1016/j.ipl.2009.04.018. Google Scholar
[27]	J. Lenstra, A. H. G. Rinnooy Kan and P. Brucker, Complexity of Machine Scheduling Problems, Annals of Discrete Mathematics, 1 (1977), 343-362. Google Scholar
[28]	M. Lai and X. Tong, A metaheuristic method for vehicle routing problem based on improved ant colony optimization and Tabu search, Journal of Industrial and Management Optimization, 8 (2012), 469-484. doi: 10.3934/jimo.2012.8.469. Google Scholar
[29]	P. Liu and L. Tang, Two-agent scheduling with linear deteriorating jobs on a single machine, Lecture Notes in Computer Science, 5092 (2008), 642-650. Google Scholar
[30]	P. Liu, X. Y. Zhou and L. X. Tang, Two-agent single-machine scheduling with position-dependent processing times, International Journal of Advanced Manufacturing Technology, 48 (2010), 325-331. doi: 10.1007/s00170-009-2259-5. Google Scholar
[31]	D. C. Li and P. H. Hsu, Solving a two-agent single-machine scheduling problem considering learning effect, Computers & Operations Research, 39 (2012), 1644-1651. doi: 10.1016/j.cor.2011.09.018. Google Scholar
[32]	W. Luo, L. Chen and G. Zhang, Approximation schemes for two-machine flow shop scheduling with two agents, Journal of Combinatorial Optimization, 24 (2012), 229-239. doi: 10.1007/s10878-011-9378-2. Google Scholar
[33]	W. Luo and L. Chen, Approximation schemes for scheduling a maintenance and linear deteriorating jobs, Journal of Industrial and Management Optimization, 8 (2012), 271-283. doi: 10.3934/jimo.2012.8.271. Google Scholar
[34]	E. Mokotoff, Algorithms for bicriteria minimization in the permutation flow shop scheduling problem, Journal of Industrial and Management Optimization, 7 (2011), 253-282. doi: 10.3934/jimo.2011.7.253. Google Scholar
[35]	G. Mosheiov, $V$-shaped policies for scheduling deteriorating jobs, Operations Research, 39 (1991), 979-991. doi: 10.1287/opre.39.6.979. Google Scholar
[36]	G. Mosheiov, Scheduling jobs under simple linear deterioration, Computers & Operations Research, 21 (1994), 653-659. doi: 10.1016/0305-0548(94)90080-9. Google Scholar
[37]	B. Mor and G. Mosheiov, Scheduling problems with two competing agents to minimize minmax and minsum earliness measures, European Journal of Operational Research, 206 (2010), 540-546. doi: 10.1016/j.ejor.2010.03.003. Google Scholar
[38]	C. T. Ng, T. C. E. Cheng and J. J. Yuan, A note on the complexity of the problem of two-agent scheduling on a single machine, Journal of Combinatorial Optimization, 12 (2006), 387-394. doi: 10.1007/s10878-006-9001-0. Google Scholar
[39]	Q. Q. Nong, T. C. E. Cheng and C. T. Ng, Two-agent scheduling to minimize the total cost, European Journal of Operational Research, 215 (2011), 39-44. doi: 10.1016/j.ejor.2011.05.041. Google Scholar
[40]	J. B. Wang and T. C. E. Cheng, Scheduling problems with the effects of deterioration and learning, Asia-Pacific Journal of Operational Research, 24 (2007), 245-261. doi: 10.1142/S021759590700122X. Google Scholar
[41]	J. B. Wang and Q. Guo, A due-date assignment problem with learning effect and deteriorating jobs, Applied Mathematical Modelling, 34 (2010), 309-313. doi: 10.1016/j.apm.2009.04.020. Google Scholar
[42]	J. B. Wang, L. H. Sun and L. Y. Sun, Single-machine total completion time scheduling with a time-dependent deterioration, Applied Mathematical Modelling, 35 (2011), 1506-1511. doi: 10.1016/j.apm.2010.09.028. Google Scholar
[43]	G. Wan, R. S. Vakati, J. Y. T. Leung and M. Pinedo, Scheduling two agents with controllable processing times, European Journal of Operational Research, 205 (2010), 528-539. doi: 10.1016/j.ejor.2010.01.005. Google Scholar
[44]	W. H. Wu, S. R. Cheng, C. C. Wu and Y. Yin, Ant colony algorithms for a two-agent scheduling with sum-of processing times-based learning and deteriorating considerations, Journal of Intelligent Manufacturing, 23 (2012), 1985-1993. doi: 10.1007/s10845-011-0525-5. Google Scholar
[45]	C. C. Wu, S. K. Huang and W. C. Lee, Two-agent scheduling with learning consideration, Computers & Industrial Engineering, 61 (2011), 1324-1335. doi: 10.1016/j.cie.2011.08.007. Google Scholar
[46]	D. L. Yang and W. H. Kuo, Single-machine scheduling with both deterioration and learning effects, Annals of Operations Research, 172 (2009), 315-327. doi: 10.1007/s10479-009-0615-3. Google Scholar
[47]	D. L. Yang and W. H. Kuo, Scheduling with deteriorating jobs and learning effects, Applied Mathematics and Computation, 218 (2011), 2069-2073. doi: 10.1016/j.amc.2011.07.023. Google Scholar
[48]	S. H. Yang and J. B. Wang, Minimizing total weighted completion time in a two-machine flow shop scheduling under simple linear deterioration, Applied Mathematics and Computation, 217 (2011), 4819-4826. doi: 10.1016/j.amc.2010.11.037. Google Scholar
[49]	S. H. Yang and D. L. Yang, Minimizing the total completion time in single-machine scheduling with aging/deteriorating effects and deteriorating maintenance activities, Computers and Mathematics with Applications, 60 (2010), 2161-2169. doi: 10.1016/j.camwa.2010.08.003. Google Scholar
[50]	Y. Yin and D. Xu, Some single-machine scheduling problems with general effects of learning and deterioration, Computers and Mathematics with Applications, 61 (2011), 100-108. doi: 10.1016/j.camwa.2010.10.036. Google Scholar
[51]	Y. Yin, S. R. Cheng and C. C. Wu, Scheduling problems with two agents and a linear non-increasing deterioration to minimize earliness penalties, Information Sciences, 189 (2012), 282-292. doi: 10.1016/j.ins.2011.11.035. Google Scholar
[52]	Y. Yin, S. R. Cheng, T. C. E. Cheng, W. H. Wu and C. C. Wu, Two-agent single-machine scheduling with release times and deadlines, International Journal of Shipping and Transport Logistics, 5 (2013), 75-94. doi: 10.1504/IJSTL.2013.050590. Google Scholar
[53]	Y. Yin, T. C. E. Cheng, J. Xu, S. R. Cheng and C. C. Wu, Single-machine scheduling with past-sequence-dependent delivery times and a linear deterioration, Journal of Industrial and Management Optimization, 9 (2013), 323-339. doi: 10.3934/jimo.2013.9.323. Google Scholar
[54]	C. L. Zhao, Q. L. Zhang and H. Y. Tang, Scheduling problems under linear deterioration, Acta Automatica Sinica, 29 (2003), 531-535. Google Scholar

show all references

References:

[1]	A. Agnetis, P. B. Mirchandani, D. Pacciarelli and A. Pacifici, Scheduling problems with two competing agents, Operations Research, 52 (2004), 229-242. doi: 10.1287/opre.1030.0092. Google Scholar
[2]	A. Agnetis, D. Pacciarelli and A. Pacifici, Multi-agent single machine scheduling, Annals of Operations Research, 150 (2007), 3-15. doi: 10.1007/s10479-006-0164-y. Google Scholar
[3]	B. Alidaee and N. K. Womer, Scheduling with time dependent processing times: Review and extensions, Journal of the Operational Research Society, 50 (1999), 711-729. Google Scholar
[4]	A. Allahverdi and F. S. Al-Anzi, Using two-machine flowshop with maximum lateness objective to model multimedia data objects scheduling problem for WWW applications, Computers and Operations Research, 29 (2002), 971-994. doi: 10.1016/S0305-0548(00)00097-6. Google Scholar
[5]	A. Bachman and A. Janiak, Scheduling Jobs with Special Type of Start Time Dependent Processing Times, Report No 34/97, Institute of Engineering Cybernetics, Wroclaw University of Technology, 1997. Google Scholar
[6]	K. R. Baker and J. C. Smith, A multiple-criterion model for machine scheduling, Journal of Scheduling, 6 (2003), 7-16. doi: 10.1023/A:1022231419049. Google Scholar
[7]	D. Ben-Arieh and O. Maimon, Annealing method for PCB assembly scheduling on two sequential machines, International Journal of Computer Integrated Manufacturing, 5 (1992), 361-367. doi: 10.1080/09511929208944543. Google Scholar
[8]	S. Browne and U. Yechiali, Scheduling deteriorating jobs on a single processor, Operations Research, 38 (1990), 495-498. doi: 10.1287/opre.38.3.495. Google Scholar
[9]	S. R. Cheng, A single-machine two-agent scheduling problem by GA approach, Asia-Pacific Journal of Operational Research, 29 (2012), 1250013, 22 pp. doi: 10.1142/S0217595912500133. Google Scholar
[10]	T. C. E. Cheng, Q. Ding and B. M. T. Lin, A concise survey of scheduling with time-dependent processing times, European Journal of Operational Research, 152 (2004), 1-13. doi: 10.1016/S0377-2217(02)00909-8. Google Scholar
[11]	T. C. E. Cheng, C. T. Ng and J. J. Yuan, Multi-agent scheduling on a single machine to minimize total weighted number of tardy jobs, Theoretical Computer Science, 362 (2006), 273-281. doi: 10.1016/j.tcs.2006.07.011. Google Scholar
[12]	T. C. E. Cheng, C. T. Ng and J. J. Yuan, Multi-agent scheduling on a single machine with max-form criteria, European Journal of Operational Research, 188 (2008), 603-609. doi: 10.1016/j.ejor.2007.04.040. Google Scholar
[13]	T. C. E. Cheng, S. R. Cheng, W. H. Wu, P. H. Hsu and C. C. Wu, A two-agent single- machine scheduling problem with truncated sum-of-processing-times-based learning considerations, Computers & Industrial Engineering, 60 (2011), 534-541. doi: 10.1016/j.cie.2010.12.008. Google Scholar
[14]	T. C. E. Cheng, W. H. Wu, S. R. Cheng and C. C. Wu, Two-agent scheduling with position- based deteriorating jobs and learning effects, Applied Mathematics and Computation, 217 (2011), 8804-8824. doi: 10.1016/j.amc.2011.04.005. Google Scholar
[15]	T. C. E. Cheng, Y. H. Chung, S. C. Liao and W. C Lee, Two-agent singe-machine scheduling with release times to minimize the total weighted completion time, Computers & Operations Research, 40 (2013), 353-361. doi: 10.1016/j.cor.2012.07.013. Google Scholar
[16]	C. Chu, A branch-and-bound algorithm to minimize total tardiness with different release dates, Naval Research Logistics, 39 (1992), 859-875. Google Scholar
[17]	A. Colorni, M. Dorigo, M. Maniezzo, I. F. J. Varela and P. Bourgine, Distributed Optimization by Ant Colonies, Proceedings of the first European Conference on Artificial Life, Pairs, 1991. Google Scholar
[18]	A. Colorni, M. Dorigo, V. Maniezzo and M. Trubian, Ant system for job-shop scheduling, Belgian Journal of Operations Research, 34 (1994), 39-53. Google Scholar
[19]	M. Dorigo, Di Caro G and L. M. Gambardella, Ant algorithms for discrete optimization, Artificial Life, 5 (1999), 137-172. doi: 10.1162/106454699568728. Google Scholar
[20]	M. Dorigo and L. M. Gambardella, Ant colony system: A cooperative learning approach to travel salesman problem, IEEE Trans Evol Computing, 1 (1997), 53-66. doi: 10.1109/4235.585892. Google Scholar
[21]	M. L. Fisher, A dual algorithm for the one-machine scheduling problem,, Math Programming, 11 (): 229. doi: 10.1007/BF01580393. Google Scholar
[22]	R. L. Graham, E. L. Lawler, J. K. Lenstra and A. H. G. Rinnooy Kan, Optimization and heuristic in deterministic sequencing and scheduling: A survey, Annals of Discrete Mathematics, 5 (1979), 287-326. doi: 10.1016/S0167-5060(08)70356-X. Google Scholar
[23]	A. Janiak, T. Krysiak and R. Trela, Scheduling problems with learning and aging effects: A survey, Decision Making in Manufacturing and Services, 5 (2011), 19-36. Google Scholar
[24]	S. Kirkpatrick, C. Gelatt and M. Vecchi, Optimization by simulated annealing, Science, 220 (1983), 671-680. doi: 10.1126/science.220.4598.671. Google Scholar
[25]	A. S. Kunnathur and S. K. Gupta, Minimizing the makespan with late start penalties added to processing times in a single facility scheduling problem, European Journal of Operation Research, 47 (1990), 56-64. doi: 10.1016/0377-2217(90)90089-T. Google Scholar
[26]	K. Lee, B. C. Choi, J. Y. T. Leung and M. L. Pinedo, Approximation algorithms for multi-agent scheduling to minimize total weighted completion time, Information Processing Letters, 109 (2009), 913-917. doi: 10.1016/j.ipl.2009.04.018. Google Scholar
[27]	J. Lenstra, A. H. G. Rinnooy Kan and P. Brucker, Complexity of Machine Scheduling Problems, Annals of Discrete Mathematics, 1 (1977), 343-362. Google Scholar
[28]	M. Lai and X. Tong, A metaheuristic method for vehicle routing problem based on improved ant colony optimization and Tabu search, Journal of Industrial and Management Optimization, 8 (2012), 469-484. doi: 10.3934/jimo.2012.8.469. Google Scholar
[29]	P. Liu and L. Tang, Two-agent scheduling with linear deteriorating jobs on a single machine, Lecture Notes in Computer Science, 5092 (2008), 642-650. Google Scholar
[30]	P. Liu, X. Y. Zhou and L. X. Tang, Two-agent single-machine scheduling with position-dependent processing times, International Journal of Advanced Manufacturing Technology, 48 (2010), 325-331. doi: 10.1007/s00170-009-2259-5. Google Scholar
[31]	D. C. Li and P. H. Hsu, Solving a two-agent single-machine scheduling problem considering learning effect, Computers & Operations Research, 39 (2012), 1644-1651. doi: 10.1016/j.cor.2011.09.018. Google Scholar
[32]	W. Luo, L. Chen and G. Zhang, Approximation schemes for two-machine flow shop scheduling with two agents, Journal of Combinatorial Optimization, 24 (2012), 229-239. doi: 10.1007/s10878-011-9378-2. Google Scholar
[33]	W. Luo and L. Chen, Approximation schemes for scheduling a maintenance and linear deteriorating jobs, Journal of Industrial and Management Optimization, 8 (2012), 271-283. doi: 10.3934/jimo.2012.8.271. Google Scholar
[34]	E. Mokotoff, Algorithms for bicriteria minimization in the permutation flow shop scheduling problem, Journal of Industrial and Management Optimization, 7 (2011), 253-282. doi: 10.3934/jimo.2011.7.253. Google Scholar
[35]	G. Mosheiov, $V$-shaped policies for scheduling deteriorating jobs, Operations Research, 39 (1991), 979-991. doi: 10.1287/opre.39.6.979. Google Scholar
[36]	G. Mosheiov, Scheduling jobs under simple linear deterioration, Computers & Operations Research, 21 (1994), 653-659. doi: 10.1016/0305-0548(94)90080-9. Google Scholar
[37]	B. Mor and G. Mosheiov, Scheduling problems with two competing agents to minimize minmax and minsum earliness measures, European Journal of Operational Research, 206 (2010), 540-546. doi: 10.1016/j.ejor.2010.03.003. Google Scholar
[38]	C. T. Ng, T. C. E. Cheng and J. J. Yuan, A note on the complexity of the problem of two-agent scheduling on a single machine, Journal of Combinatorial Optimization, 12 (2006), 387-394. doi: 10.1007/s10878-006-9001-0. Google Scholar
[39]	Q. Q. Nong, T. C. E. Cheng and C. T. Ng, Two-agent scheduling to minimize the total cost, European Journal of Operational Research, 215 (2011), 39-44. doi: 10.1016/j.ejor.2011.05.041. Google Scholar
[40]	J. B. Wang and T. C. E. Cheng, Scheduling problems with the effects of deterioration and learning, Asia-Pacific Journal of Operational Research, 24 (2007), 245-261. doi: 10.1142/S021759590700122X. Google Scholar
[41]	J. B. Wang and Q. Guo, A due-date assignment problem with learning effect and deteriorating jobs, Applied Mathematical Modelling, 34 (2010), 309-313. doi: 10.1016/j.apm.2009.04.020. Google Scholar
[42]	J. B. Wang, L. H. Sun and L. Y. Sun, Single-machine total completion time scheduling with a time-dependent deterioration, Applied Mathematical Modelling, 35 (2011), 1506-1511. doi: 10.1016/j.apm.2010.09.028. Google Scholar
[43]	G. Wan, R. S. Vakati, J. Y. T. Leung and M. Pinedo, Scheduling two agents with controllable processing times, European Journal of Operational Research, 205 (2010), 528-539. doi: 10.1016/j.ejor.2010.01.005. Google Scholar
[44]	W. H. Wu, S. R. Cheng, C. C. Wu and Y. Yin, Ant colony algorithms for a two-agent scheduling with sum-of processing times-based learning and deteriorating considerations, Journal of Intelligent Manufacturing, 23 (2012), 1985-1993. doi: 10.1007/s10845-011-0525-5. Google Scholar
[45]	C. C. Wu, S. K. Huang and W. C. Lee, Two-agent scheduling with learning consideration, Computers & Industrial Engineering, 61 (2011), 1324-1335. doi: 10.1016/j.cie.2011.08.007. Google Scholar
[46]	D. L. Yang and W. H. Kuo, Single-machine scheduling with both deterioration and learning effects, Annals of Operations Research, 172 (2009), 315-327. doi: 10.1007/s10479-009-0615-3. Google Scholar
[47]	D. L. Yang and W. H. Kuo, Scheduling with deteriorating jobs and learning effects, Applied Mathematics and Computation, 218 (2011), 2069-2073. doi: 10.1016/j.amc.2011.07.023. Google Scholar
[48]	S. H. Yang and J. B. Wang, Minimizing total weighted completion time in a two-machine flow shop scheduling under simple linear deterioration, Applied Mathematics and Computation, 217 (2011), 4819-4826. doi: 10.1016/j.amc.2010.11.037. Google Scholar
[49]	S. H. Yang and D. L. Yang, Minimizing the total completion time in single-machine scheduling with aging/deteriorating effects and deteriorating maintenance activities, Computers and Mathematics with Applications, 60 (2010), 2161-2169. doi: 10.1016/j.camwa.2010.08.003. Google Scholar
[50]	Y. Yin and D. Xu, Some single-machine scheduling problems with general effects of learning and deterioration, Computers and Mathematics with Applications, 61 (2011), 100-108. doi: 10.1016/j.camwa.2010.10.036. Google Scholar
[51]	Y. Yin, S. R. Cheng and C. C. Wu, Scheduling problems with two agents and a linear non-increasing deterioration to minimize earliness penalties, Information Sciences, 189 (2012), 282-292. doi: 10.1016/j.ins.2011.11.035. Google Scholar
[52]	Y. Yin, S. R. Cheng, T. C. E. Cheng, W. H. Wu and C. C. Wu, Two-agent single-machine scheduling with release times and deadlines, International Journal of Shipping and Transport Logistics, 5 (2013), 75-94. doi: 10.1504/IJSTL.2013.050590. Google Scholar
[53]	Y. Yin, T. C. E. Cheng, J. Xu, S. R. Cheng and C. C. Wu, Single-machine scheduling with past-sequence-dependent delivery times and a linear deterioration, Journal of Industrial and Management Optimization, 9 (2013), 323-339. doi: 10.3934/jimo.2013.9.323. Google Scholar
[54]	C. L. Zhao, Q. L. Zhang and H. Y. Tang, Scheduling problems under linear deterioration, Acta Automatica Sinica, 29 (2003), 531-535. Google Scholar

[1]	Miao Yu. A solution of TSP based on the ant colony algorithm improved by particle swarm optimization. Discrete & Continuous Dynamical Systems - S, 2019, 12 (4&5) : 979-987. doi: 10.3934/dcdss.2019066
[2]	Hongwei Li, Yuvraj Gajpal, C. R. Bector. A survey of due-date related single-machine with two-agent scheduling problem. Journal of Industrial & Management Optimization, 2020, 16 (3) : 1329-1347. doi: 10.3934/jimo.2019005
[3]	Yunqing Zou, Zhengkui Lin, Dongya Han, T. C. Edwin Cheng, Chin-Chia Wu. Two-agent integrated scheduling of production and distribution operations with fixed departure times. Journal of Industrial & Management Optimization, 2021 doi: 10.3934/jimo.2021005
[4]	Jean-Paul Arnaout, Georges Arnaout, John El Khoury. Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem. Journal of Industrial & Management Optimization, 2016, 12 (4) : 1215-1225. doi: 10.3934/jimo.2016.12.1215
[5]	Lan Luo, Zhe Zhang, Yong Yin. Simulated annealing and genetic algorithm based method for a bi-level seru loading problem with worker assignment in seru production systems. Journal of Industrial & Management Optimization, 2021, 17 (2) : 779-803. doi: 10.3934/jimo.2019134
[6]	T. W. Leung, Chi Kin Chan, Marvin D. Troutt. A mixed simulated annealing-genetic algorithm approach to the multi-buyer multi-item joint replenishment problem: advantages of meta-heuristics. Journal of Industrial & Management Optimization, 2008, 4 (1) : 53-66. doi: 10.3934/jimo.2008.4.53
[7]	Le Thi Hoai An, Tran Duc Quynh, Kondo Hloindo Adjallah. A difference of convex functions algorithm for optimal scheduling and real-time assignment of preventive maintenance jobs on parallel processors. Journal of Industrial & Management Optimization, 2014, 10 (1) : 243-258. doi: 10.3934/jimo.2014.10.243
[8]	Yukang He, Zhengwen He, Nengmin Wang. Tabu search and simulated annealing for resource-constrained multi-project scheduling to minimize maximal cash flow gap. Journal of Industrial & Management Optimization, 2021, 17 (5) : 2451-2474. doi: 10.3934/jimo.2020077
[9]	Mostafa Abouei Ardakan, A. Kourank Beheshti, S. Hamid Mirmohammadi, Hamed Davari Ardakani. A hybrid meta-heuristic algorithm to minimize the number of tardy jobs in a dynamic two-machine flow shop problem. Numerical Algebra, Control & Optimization, 2017, 7 (4) : 465-480. doi: 10.3934/naco.2017029
[10]	Ji-Bo Wang, Mengqi Liu, Na Yin, Ping Ji. Scheduling jobs with controllable processing time, truncated job-dependent learning and deterioration effects. Journal of Industrial & Management Optimization, 2017, 13 (2) : 1025-1039. doi: 10.3934/jimo.2016060
[11]	Guangzhou Chen, Guijian Liu, Jiaquan Wang, Ruzhong Li. Identification of water quality model parameters using artificial bee colony algorithm. Numerical Algebra, Control & Optimization, 2012, 2 (1) : 157-165. doi: 10.3934/naco.2012.2.157
[12]	Ling Lin, Dong He, Zhiyi Tan. Bounds on delay start LPT algorithm for scheduling on two identical machines in the $l_p$ norm. Journal of Industrial & Management Optimization, 2008, 4 (4) : 817-826. doi: 10.3934/jimo.2008.4.817
[13]	Jiping Tao, Ronghuan Huang, Tundong Liu. A $2.28$-competitive algorithm for online scheduling on identical machines. Journal of Industrial & Management Optimization, 2015, 11 (1) : 185-198. doi: 10.3934/jimo.2015.11.185
[14]	Harish Garg. Solving structural engineering design optimization problems using an artificial bee colony algorithm. Journal of Industrial & Management Optimization, 2014, 10 (3) : 777-794. doi: 10.3934/jimo.2014.10.777
[15]	Didem Cinar, José António Oliveira, Y. Ilker Topcu, Panos M. Pardalos. A priority-based genetic algorithm for a flexible job shop scheduling problem. Journal of Industrial & Management Optimization, 2016, 12 (4) : 1391-1415. doi: 10.3934/jimo.2016.12.1391
[16]	Jingwen Zhang, Wanjun Liu, Wanlin Liu. An efficient genetic algorithm for decentralized multi-project scheduling with resource transfers. Journal of Industrial & Management Optimization, 2020 doi: 10.3934/jimo.2020140
[17]	Cuixia Miao, Yuzhong Zhang. Scheduling with step-deteriorating jobs to minimize the makespan. Journal of Industrial & Management Optimization, 2019, 15 (4) : 1955-1964. doi: 10.3934/jimo.2018131
[18]	Wenchang Luo, Lin Chen. Approximation schemes for scheduling a maintenance and linear deteriorating jobs. Journal of Industrial & Management Optimization, 2012, 8 (2) : 271-283. doi: 10.3934/jimo.2012.8.271
[19]	Mohsen Abdolhosseinzadeh, Mir Mohammad Alipour. Design of experiment for tuning parameters of an ant colony optimization method for the constrained shortest Hamiltonian path problem in the grid networks. Numerical Algebra, Control & Optimization, 2021, 11 (2) : 321-332. doi: 10.3934/naco.2020028
[20]	Pikkala Vijaya Laxmi, Singuluri Indira, Kanithi Jyothsna. Ant colony optimization for optimum service times in a Bernoulli schedule vacation interruption queue with balking and reneging. Journal of Industrial & Management Optimization, 2016, 12 (4) : 1199-1214. doi: 10.3934/jimo.2016.12.1199

2020 Impact Factor: 1.801

American Institute of Mathematical Sciences

A time-dependent scheduling problem to minimize the sum of the total weighted tardiness among two agents

References:

References:

Tools

Metrics

Other articles
by authors

Tools

Metrics

Other articles
by authors

American Institute of Mathematical Sciences

A time-dependent scheduling problem to minimize the sum of the total weighted tardiness among two agents

References:

References:

Tools

Metrics

Other articlesby authors

Tools

Metrics

Other articlesby authors

Other articles
by authors

Other articles
by authors