Multi-period lot sizing and job shop scheduling with compressible process times for multilevel product structures

Karimi-Nasab, M.; Seyedhoseini, S. M.; Modarres, Mohammad; Heidari, M

doi:10.1080/00207543.2013.825743

Cited by 11 publications

(5 citation statements)

References 26 publications

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“…Reviews of research results on scheduling models considering resource-dependent processing times consist of Nowicki and Zdrzałka (1990), Chen, Potts, and Woeginger (1999), Shabtay and Steiner (2007). More recent research with controllable processing time, we can see Su and Lien (2009), Mokhtari, Abadi, and Cheraghalikhani (2011), Karimi-Nasab and Ghomi (2012, Karimi-Nasab et al (2013), and Yang, Cheng, and Yang (2014). For recent papers, considering scheduling problems with due-window and resource allocation, we can refer to Ji et al (2013), and .…”

Section: Introductionmentioning

confidence: 97%

Due-window assignment and scheduling with general position-dependent processing times involving a deteriorating and compressible maintenance activity

Zhu

Zhou

et al. 2015

International Journal of Production Research

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In this paper, we consider common due-window assignment and scheduling problems with general position-dependent processing times involving deteriorating and compressible maintenance activity on a single machine. Two models associated with maintenance activity are examined in this article, in which the maintenance length is assumed to be either time-dependent and compressible or position-dependent and compressible. The objective is to find jointly the location and size of due-window, position of maintenance as well as resource amount allocated to it, and job sequence to minimise a total cost function based on earliness, tardiness, window location, window size and resource cost. We show that the problem considered in each of the two models' setting can be optimally solved with polynomial time algorithm by reducing to assignment problem. Finally, two examples are provided to illustrate the solution procedures.

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Section: Introductionmentioning

confidence: 97%

Due-window assignment and scheduling with general position-dependent processing times involving a deteriorating and compressible maintenance activity

Zhu

Zhou

et al. 2015

International Journal of Production Research

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“…is a fixed and constant value) (Pinedo 2002), however, we often encounter variable job processing times settings in which the processing time of a job may be changed due to the phenomenon of learning and/or deterioration and/or resource allocation (controllable processing time, compressible process times Karimi-Nasab et al (2013) and Karimi-Nasab and Sabri-Laghaie (2014)). Extensive surveys of different sequencing and scheduling models and problems involving jobs with variable processing times (i.e.…”

Section: Introductionmentioning

confidence: 97%

Due date assignment and convex resource allocation scheduling with variable job processing times

Sun¹,

Cui

Chen

et al. 2015

International Journal of Production Research

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This is a study of a earliness and tardiness sequencing and scheduling problem on a single machine. The processing time for job J j depends on its position in a sequence, its starting time, and its allocation of non-renewable resource. For three due date assignment methods i.e. the common due date, the slack due date and the unrestricted due date our goal is to find the optimal schedule, due dates, and resource allocations of jobs. We prove that three versions of the problem can be solved in polynomial time, respectively.

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“…The scheduling problem with random orders has been becoming increasingly important for smart manufacturing. Traditionally, the manufacturing factory focuses on reducing production cost [ 2 ]. However, the goal of a smart factory involves not only minimizing manufacturing cost, but also maximizing customer satisfaction.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Production and Logistics Self-Adaption Scheduling Based on Information Entropy Theory

Yang

Cao

et al. 2020

Sensors

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In recent years, the individualized demand of customers brings small batches and diversification of orders towards enterprises. The application of enabling technologies in the factory, such as the industrial Internet of things (IIoT) and cloud manufacturing (CMfg), enhances the ability of customer requirement automatic elicitation and the manufacturing process control. The job shop scheduling problem with a random job arrival time dramatically increases the difficulty in process management. Thus, how to collaboratively schedule the production and logistics resources in the shop floor is very challenging, and it has a fundamental and practical significance of achieving the competitiveness for an enterprise. To address this issue, the real-time model of production and logistics resources is built firstly. Then, the task entropy model is built based on the task information. Finally, the real-time self-adaption collaboration of production and logistics resources is realized. The proposed algorithm is carried out based on a practical case to evaluate its effectiveness. Experimental results show that our proposed algorithm outperforms three existing algorithms.

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Multi-period lot sizing and job shop scheduling with compressible process times for multilevel product structures

Cited by 11 publications

References 26 publications

Due-window assignment and scheduling with general position-dependent processing times involving a deteriorating and compressible maintenance activity

Due-window assignment and scheduling with general position-dependent processing times involving a deteriorating and compressible maintenance activity

Due date assignment and convex resource allocation scheduling with variable job processing times

Real-Time Production and Logistics Self-Adaption Scheduling Based on Information Entropy Theory

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