Predicting the performance of rescheduling strategies for parallel machine systems

Abstract

In dynamic, stochastic manufacturing systems, production planners and manufacturing engineers can benefit from understanding how rescheduling strategies affect system performance. This knowledge will help these experts design and operate better manufacturing planning and control systems. This paper presents new analytical models that can predict the performance of rescheduling strategies and quantify the trade-offs between different performance measures. In the parallel machine systems under consideration, jobs of different types arrive dynamically, and setups occur when production changes from one job type to another. Three rescheduling strategies are studied: periodic, hybrid, and event-driven based on the queue size. The scheduling algorithm groups jobs of the same type in batches to eliminate unnecessary setups. The analytical models require less computational effort than simulation models, and experimental results show that they accurately estimate important performance measures like average flow time, machine utilization, and setup frequency.

Flow shop rescheduling under different types of disruption

“…Many production stages consist of several of machines in parallel (Pinedo, 2008). Vieira et al (2000) present analytical models that predict the performance of rescheduling strategies for parallel machine systems. They consider dynamic job arrivals and setups between job families.…”

“…In the rescheduling literature, a plethora of approaches and techniques can be found to deal with uncertainties, focusing mainly on machine breakdowns, new job arrivals and stochastic process times. However, the great part of the existing work addresses these disruptions only independently (Church and Uzsoy, 1992;Allahverdi, 1996;Mehta and Uzsoy, 1999;Vieira et al, 2000;Hall and Potts, 2004;Rangsaritratsamee et al, 2004;Arnaut and Rabadi, 2008;Kopanos et al, 2008). These sources of disturbances and many others such as order cancelations, priority and release time changes due to material unavailability, may aect the current schedule simultaneously.…”

Scheduling a Dynamic Aircraft Repair Shop with Limited Repair Resources

“…How to solve static sub-problems and how to connect them using rescheduling strategies are the main aspects of the dynamic scheduling research. Although we are not aware of using dynamic scheduling in a repair system, it has been successfully applied to a variety of scheduling problems including single machine (Ovacik & Uzsoy, 1994;O'Donovan et al, 1999;Cowling & Johansson, 2002), parallel machines (Vieira, Hermann, & Lin, 2000;Ovacik & Uzsoy, 1995), and job shop (Sabuncuoglu & Bayiz, 2000;Liu, Ong, & Ng, 2005;Vinod & Sridharan, 2011).…”

Flexible flow shop scheduling with stochastic processing times: A decomposition-based approach

“…A hybrid policy reschedules periodically as well as when a disruption arises. Vieira et al (2000) investigated 6 the performance of three rescheduling strategies for parallel machine systems with machine failure. They found that although all the three strategies exhibited similar performance, the hybrid strategy decreased flow time slightly for it performed rescheduling more often.…”