Predictive-Reactive Rescheduling for New Order Arrivals with Optimal Dynamic Pegging

Shokraneh K. Moghaddam, Kazuhiro Saitou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a new predictive-reactive rescheduling method for adjusting production schedules in response to the unplanned arrival of new orders in multi-level production. It is based on the concept of dynamic pegging, which enables the reassignment of the Work-In-Progress (WIP) to the existing or newly arrived orders at the time of rescheduling. Extending our previous work on reactive rescheduling with dynamic pegging, the new approach incorporates a probabilistic predictive model of new order arrival in the initial scheduling at the begging of the scheduling horizon. A Mixed Integer Programming (MIP) model is developed for two-phase, predictive-reactive scheduling before and after the arrival of a new order that follows an exponential distribution. The MIP model is solved for two periods. In the predictive phase before the new order arrival, the best schedule is achieved based on the expected arrival time for a new order. In the reactive phase after the new order arrival, the best schedule is created based on the dynamic pegging approach. Using a simple example, the proposed predictive-reactive rescheduling is compared with the reactive-only rescheduling in our previous work, with sampled arrivals of new orders. It is demonstrated the proposed approach performs statistically better than the reactive-only approach, especially during the reacting phase.

Original languageEnglish
Title of host publication2020 IEEE 16th International Conference on Automation Science and Engineering, CASE 2020
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages710-715
Number of pages6
ISBN (Electronic)9781728169040
DOIs
Publication statusPublished - Aug 2020
Externally publishedYes
Event16th IEEE International Conference on Automation Science and Engineering, CASE 2020 - Hong Kong, Hong Kong
Duration: 20 Aug 202021 Aug 2020

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2020-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference16th IEEE International Conference on Automation Science and Engineering, CASE 2020
Country/TerritoryHong Kong
CityHong Kong
Period20/08/2021/08/20

Keywords

  • dynamic pegging
  • predictive-reactive scheduling
  • stochastic order arrivals

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