One-machine rescheduling heuristics with efficiency and stability as criteria
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An effective two-stage algorithm based on convolutional neural network for the bi-objective flexible job shop scheduling problem with machine breakdown
2022, Expert Systems with ApplicationsDynamic scheduling method for integrated process planning and scheduling problem with machine fault
2022, Robotics and Computer-Integrated ManufacturingA novel predictive-reactive rescheduling method for products assembly lines with optimal dynamic pegging
2022, Computers and Industrial EngineeringA three-stage decomposition algorithm for decentralized multi-project scheduling under uncertainty
2021, Computers and Industrial EngineeringCitation Excerpt :The content of the information exchanges was then utilized to obtain a baseline schedule (cf. Confessore, Giordani, & Rismondo, 2007; Homberger, 2012; Adhau & Mittal, 2013). The baseline schedule served as a basis for planning external tasks such as preventive maintenance, procurement of materials, and committing to ship dates (Wu, Storer, & Chang, 1993). In multi-project environments, it is necessary to seek a schedule that can be agreed upon by all parties involved (e.g., clients and suppliers, as well as workers and other personnel) before execution (Herroelen & Leus, 2004).
Predictive-reactive strategy for identical parallel machine rescheduling
2021, Computers and Operations ResearchCitation Excerpt :To the best of our knowledge, there is not any rescheduling problem in the literature that discussed this criterion. The efficiency usually measures the performance of a scheduling system, but, in dynamic environments, the impact of jobs deviation is also measured, referred to as stability measure (Wu et al., 1993; Pfeiffer et al., 2007; Zhang et al., 2013). The stability measure evaluates the impact of disruptions induced by moving job during a rescheduling event (Rangsaritratsamee et al., 2004; Tighazoui et al., 2021).
Modelling and comparison of stability metrics for a re-optimisation approach of the Inventory Routing Problem under demand uncertainty
2021, EURO Journal on Transportation and LogisticsCitation Excerpt :Within these fields, a special care is given to problems modelled over a rolling horizon: while they do not carry out re-optimisation as such, they often deal with uncertainty with a real concern for stability. Stability when re-optimising was first tackled in the scheduling field by Wu et al. (1993). In this work, heuristics are proposed to re-schedule jobs on one machine when a disruption occurs, e.g. a machine failure, with two objectives: efficiency (i.e. makespan) and stability.
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S. David Wu is an Associate Professor of Industrial Engineering at Lehigh University. His primary research areas include production planning and scheduling, combinatorial optimization, and telecommunication. His recent work has been in the area of scheduling and control of failure-prone production systems. He holds a M.S. and a Ph.D. degrees, both in Industrial Engineering, from the Pennsylvania State University.
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Robert H. Storer is an Assistant Professor of Industrial Engineering at Lehigh University. He holds a Ph.D. in Industrial and Systems Engineering and a M.S. in Operations Research from the Georgia Institute of Technology, and a B.S. in Industrial Engineering and Operations Research from the University of Michigan. His research interests involve the application of statistics and operations research to industrial problems. Research thrusts are in the areas of statistical methods for improvement of continuous processes, and heuristic approaches to combinatorial problems.
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Pei-Chann Chang is an Associate Professor of Industrial Engineering at Yuan-Tze Institute of Technology, Tao-Yuan, Taiwan, Republic of China. His primary research area is in production scheduling and control. He holds an M.S. and a Ph.D. degrees in Industrial Engineering from Lehigh University.