Single-machine scheduling and common due date assignment with potential machine disruption

This paper studies a single-machine due date assignment and scheduling problem in a disruptive environment, where a machine disruption may occur at a particular time that will last for a period of time with a certain probability, and the job due dates are determined by the decision-maker using the p...

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Veröffentlicht in:	International journal of production research Jg. 56; H. 3; S. 1345 - 1360
Hauptverfasser:	Xiong, Xiaoyun, Wang, Dujuan, Edwin Cheng, T.C., Wu, Chin-Chia, Yin, Yunqiang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Taylor & Francis LLC 01.02.2018
Schlagworte:	Adaptive algorithms Adaptive search techniques Algorithms Cost analysis Decision making Job shops Mathematical analysis Polynomials Production scheduling Scheduling Search algorithms Sequential scheduling
ISSN:	0020-7543, 1366-588X
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Abstract	This paper studies a single-machine due date assignment and scheduling problem in a disruptive environment, where a machine disruption may occur at a particular time that will last for a period of time with a certain probability, and the job due dates are determined by the decision-maker using the popular common due date assignment method. The goal is to determine jointly the optimal job sequence and the common due date so as to minimise the expected value of an integrated cost function that includes the earliness, tardiness and due date assignment costs. We analyse the computational complexity status of various cases of the problem, and develop pseudo-polynomial-time solution algorithms, randomised adaptive search algorithms, and fully polynomial-time approximation schemes for them, if viable. Finally, we conduct extensive numerical testing to assess the performance of the proposed algorithms.
AbstractList	This paper studies a single-machine due date assignment and scheduling problem in a disruptive environment, where a machine disruption may occur at a particular time that will last for a period of time with a certain probability, and the job due dates are determined by the decision-maker using the popular common due date assignment method. The goal is to determine jointly the optimal job sequence and the common due date so as to minimise the expected value of an integrated cost function that includes the earliness, tardiness and due date assignment costs. We analyse the computational complexity status of various cases of the problem, and develop pseudo-polynomial-time solution algorithms, randomised adaptive search algorithms, and fully polynomial-time approximation schemes for them, if viable. Finally, we conduct extensive numerical testing to assess the performance of the proposed algorithms.
Author	Xiong, Xiaoyun Edwin Cheng, T.C. Wu, Chin-Chia Wang, Dujuan Yin, Yunqiang
Author_xml	– sequence: 1 givenname: Xiaoyun surname: Xiong fullname: Xiong, Xiaoyun organization: Faculty of Science, Kunming University of Science and Technology, Kunming, China – sequence: 2 givenname: Dujuan surname: Wang fullname: Wang, Dujuan organization: School of Management Science and Engineering, Dalian University of Technology, Dalian, China., Transportation Management College, Dalian Maritime University, Dalian, China – sequence: 3 givenname: T.C. surname: Edwin Cheng fullname: Edwin Cheng, T.C. organization: Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Kowloon, Hong Kong – sequence: 4 givenname: Chin-Chia surname: Wu fullname: Wu, Chin-Chia organization: Department of Statistics, Feng Chia University, Taichung, Taiwan – sequence: 5 givenname: Yunqiang surname: Yin fullname: Yin, Yunqiang organization: Faculty of Science, Kunming University of Science and Technology, Kunming, China
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SubjectTerms	Adaptive algorithms Adaptive search techniques Algorithms Cost analysis Decision making Job shops Mathematical analysis Polynomials Production scheduling Scheduling Search algorithms Sequential scheduling
Title	Single-machine scheduling and common due date assignment with potential machine disruption
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