CON/SLK due date assignment and scheduling on a single machine with two agents

We consider scheduling problems involving two agents (agents A and B), each having a set of jobs that compete for the use of a common machine to process their respective jobs. The due dates of the A‐jobs are decision variables, which are determined by using the common (CON) or slack (SLK) due date a...

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Veröffentlicht in:	Naval research logistics Jg. 63; H. 5; S. 416 - 429
Hauptverfasser:	Yin, Yunqiang, Wang, Du-Juan, Wu, Chin-Chia, Cheng, T.C.E.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Blackwell Publishing Ltd 01.08.2016 Wiley Subscription Services, Inc
Schlagworte:	Algorithms Completion time Criteria due date assignment Due dates Logistics Mathematical analysis Navy Scheduling two agents
ISSN:	0894-069X, 1520-6750
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Abstract	We consider scheduling problems involving two agents (agents A and B), each having a set of jobs that compete for the use of a common machine to process their respective jobs. The due dates of the A‐jobs are decision variables, which are determined by using the common (CON) or slack (SLK) due date assignment methods. Each agent wants to minimize a certain performance criterion depending on the completion times of its jobs only. Under each due date assignment method, the criterion of agent A is always the same, namely an integrated criterion consisting of the due date assignment cost and the weighted number of tardy jobs. Several different criteria are considered for agent B, including the maxima of regular functions (associated with each job), the total (weighted) completion time, and the weighted number of tardy jobs. The overall objective is to minimize the performance criterion of agent A, while keeping the objective value of agent B no greater than a given limit. We analyze the computational complexity, and devise polynomial or pseudo‐polynomial dynamic programming algorithms for the considered problems. We also convert, if viable, any of the devised pseudopolynomial dynamic programming algorithms into a fully polynomial‐time approximation scheme. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 416–429, 2016
AbstractList	We consider scheduling problems involving two agents (agents A and B), each having a set of jobs that compete for the use of a common machine to process their respective jobs. The due dates of the A-jobs are decision variables, which are determined by using the common (CON) or slack (SLK) due date assignment methods. Each agent wants to minimize a certain performance criterion depending on the completion times of its jobs only. Under each due date assignment method, the criterion of agent A is always the same, namely an integrated criterion consisting of the due date assignment cost and the weighted number of tardy jobs. Several different criteria are considered for agent B, including the maxima of regular functions (associated with each job), the total (weighted) completion time, and the weighted number of tardy jobs. The overall objective is to minimize the performance criterion of agent A, while keeping the objective value of agent B no greater than a given limit. We analyze the computational complexity, and devise polynomial or pseudo-polynomial dynamic programming algorithms for the considered problems. We also convert, if viable, any of the devised pseudopolynomial dynamic programming algorithms into a fully polynomial-time approximation scheme. Naval Research Logistics 63: 416-429, 2016 We consider scheduling problems involving two agents (agents A and B), each having a set of jobs that compete for the use of a common machine to process their respective jobs. The due dates of the A‐jobs are decision variables, which are determined by using the common (CON) or slack (SLK) due date assignment methods. Each agent wants to minimize a certain performance criterion depending on the completion times of its jobs only. Under each due date assignment method, the criterion of agent A is always the same, namely an integrated criterion consisting of the due date assignment cost and the weighted number of tardy jobs. Several different criteria are considered for agent B, including the maxima of regular functions (associated with each job), the total (weighted) completion time, and the weighted number of tardy jobs. The overall objective is to minimize the performance criterion of agent A, while keeping the objective value of agent B no greater than a given limit. We analyze the computational complexity, and devise polynomial or pseudo‐polynomial dynamic programming algorithms for the considered problems. We also convert, if viable, any of the devised pseudopolynomial dynamic programming algorithms into a fully polynomial‐time approximation scheme. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 416–429, 2016 We consider scheduling problems involving two agents (agents A and B ), each having a set of jobs that compete for the use of a common machine to process their respective jobs. The due dates of the A ‐jobs are decision variables, which are determined by using the common ( CON ) or slack ( SLK ) due date assignment methods. Each agent wants to minimize a certain performance criterion depending on the completion times of its jobs only. Under each due date assignment method, the criterion of agent A is always the same, namely an integrated criterion consisting of the due date assignment cost and the weighted number of tardy jobs. Several different criteria are considered for agent B , including the maxima of regular functions (associated with each job), the total (weighted) completion time, and the weighted number of tardy jobs. The overall objective is to minimize the performance criterion of agent A , while keeping the objective value of agent B no greater than a given limit. We analyze the computational complexity, and devise polynomial or pseudo‐polynomial dynamic programming algorithms for the considered problems. We also convert, if viable, any of the devised pseudopolynomial dynamic programming algorithms into a fully polynomial‐time approximation scheme. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 416–429, 2016
Author	Wang, Du-Juan Cheng, T.C.E. Wu, Chin-Chia Yin, Yunqiang
Author_xml	– sequence: 1 givenname: Yunqiang surname: Yin fullname: Yin, Yunqiang organization: Faculty of Science, Kunming University of Science and Technology, 650093, Kunming, China – sequence: 2 givenname: Du-Juan surname: Wang fullname: Wang, Du-Juan email: wangdujuan@dlut.edu.cn, wangdujuan@dlut.edu.cn organization: Transportation Management College, Dalian Maritime University, 116023, Dalian, China – sequence: 3 givenname: Chin-Chia surname: Wu fullname: Wu, Chin-Chia organization: Department of Statistics, Feng Chia University, Taichung, Taiwan – sequence: 4 givenname: T.C.E. surname: Cheng fullname: Cheng, T.C.E. organization: Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Kowloon, Hung Hom, Hong Kong
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References_xml	– reference: S.S. Li, J.J. Yuan, Unbounded parallel-batching scheduling with two competitive agents, J Scheduling 15 (2012), 629-640. – reference: Y. Yin, S.R. Cheng, T.C.E. Cheng, W.H. Wu, C.C. Wu, Two-agent single-machine scheduling with release times and deadlines, Int J Ship Trans Log 5 (2013), 75-94. – reference: P.J. Brewer, C.R. Plott, A binary conflict ascending price (BICAP) mechanism for the decentralized allocation of the right to use railroad tracks, Int J Ind Org 14 (1996), 857-886. – reference: E. Gerstl, G. Mosheiov, Single machine just-in-time scheduling problems with two competing agents, Naval Res Logist 61 (2014), 1-16. – reference: C. Pessan, J.-L. Bouquard, E. Neron, An unrelated parallel machines model for an industrial production resetting problem, Eur J Ind Eng 2 (2008), 153-171. – reference: B. Mor, G. Mosheiov, Scheduling problems with two competing agents to minimize minmax and minsum earliness measures, Eur J Oper Res 206 (2010), 540-546. – reference: D. Wang, Y. Yin, S.R. Cheng, T.C.E. Cheng, C.C. Wu, Due date assignment and scheduling on a single machine with two competing agents, Int J Prod Res 54 (2016), 1152-1169. – reference: Y. Yin, Y. Wang, T.C.E. Cheng, D.J. Wang, C.C. Wu, Two-agent single-machine scheduling to minimize the batch delivery cost, Comput Ind Eng 92 (2016), 16-30. – reference: P. Perez-Gonzalez, J.M. Framinan, A common framework and taxonomy for multicriteria scheduling problem with interfering and competing jobs: Multi-agent scheduling problems, Eur J Oper Res 235 (2014), 1-16. – reference: A. Agnetis, "Multiagent Scheduling Problems", Tutorials in Operations Research: New Directions in: P.B. Mirchandani and J. Cole Smith (Editors). Informatics, Optimization, Logistics, and Production, INFORMS, Catonsville, 2012, pp. 151-170. – reference: M.J. Soomer, G.J. Franx, Scheduling aircraft landings using airlines preferences, Eur J Oper Res 190 (2008), 277-291. – reference: G. Knotts, M. Dror, B.C. Hartman, Agent-based project scheduling, IIE Trans 32 (2000), 387-401. – reference: M.Y. Kovalyov, Improving the complexities of approximation algorithms for optimization problems, Oper Res Lett 17 (1995), 85-87. – reference: V. Gordon, V. Strusevich, A. Dolgui, Scheduling with due date assignment under special conditions on job processing, J Scheduling 15 (2012), 447-456. – reference: A. Agnetis, J.C. Billaut, S. Gawiejnowicz, D. Pacciarelli, A. Soukhal, Multiagent scheduling: Models and algorithms. Springer, Heidelberg, 2014. – reference: Y. Yin, S.R. Cheng, T.C.E. Cheng, D.J. Wang, C.C. Wu, Just-in-time scheduling with two competing agents on unrelated parallel machines, Omega 63 (2016), 41-47. – reference: M.Y. Kovalyov, A. Oulamara, A. Soukhal, Two-agent scheduling with agent specific batches on an unbounded serial batching machine, J Scheduling 18 (2015), 423-434. – reference: G. Wan, R.S. Vakati, J.Y.T. Leung, M. Pinedo, Scheduling two agents with controllable processing times, Eur J Oper Res 205 (2010), 528-539. – reference: J.Y.T. Leung, M. Pinedo, G.H. Wan, Competitive two agents scheduling and its applications, Oper Res 58 (2010), 458-469. – reference: A. Agnetis, P.B. Mirchandani, D. Pacciarelli, A. Pacifici, Scheduling problems with two competing agents, Oper Res 52 (2004), 229-242. – reference: K.R. Baker, J.C. Smith, A multiple-criterion model for machine scheduling, J Scheduling 6 (2003), 7-16. – reference: Y. Yin, T.C.E. Cheng, X. Yang, C.C. 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Snippet	We consider scheduling problems involving two agents (agents A and B), each having a set of jobs that compete for the use of a common machine to process their... We consider scheduling problems involving two agents (agents A and B ), each having a set of jobs that compete for the use of a common machine to process their...
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SubjectTerms	Algorithms Completion time Criteria due date assignment Due dates Logistics Mathematical analysis Navy Scheduling two agents
Title	CON/SLK due date assignment and scheduling on a single machine with two agents
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