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Towards Predictive and Reactive Job Shop Scheduling: A Hybrid Approach in Flexible Manufacturing Systems.

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Title: Towards Predictive and Reactive Job Shop Scheduling: A Hybrid Approach in Flexible Manufacturing Systems.
Authors: Rahman, Azrul Azwan Abdul1 azrulazwan@utem.edu.my, Adam, Muhamad Alif1, Adeboye, Oluwamayowa Joshua1, Rahman, Muhamad Arfauz A.2
Source: Jordan Journal of Mechanical & Industrial Engineering. Mar2026, Vol. 20 Issue 1, p71-86. 16p.
Subjects: Flexible manufacturing systems, Discrete event simulation, Hybrid computer simulation, Scheduling, Genetic algorithms, Production scheduling
Abstract (English): In the contemporary manufacturing landscape, unpredictable shop-floor disturbances and shortened product life cycles significantly challenge traditional scheduling methods, often leading to missed due dates and inefficient resource utilization. This study addresses these challenges by proposing a robust predictive--reactive scheduling framework designed for flexible manufacturing systems. The methodology utilizes a hybrid simulation--optimization approach, integrating discrete-event simulation to map real-time system states with a genetic-algorithm-based optimizer to identify high-performing scheduling policies. The framework is uniquely capable of dynamically generating and evaluating alternative dispatch sequences, enabling rapid recovery from operational disruptions such as equipment failure or order changes with minimal deviation from planned workflows. To enhance optimization efficiency, the model incorporates a permutation-based path generator and complexity filters that constrain the search space for the genetic algorithm. Case-study experiments conducted within a reconfigurable manufacturing context demonstrate that the proposed approach significantly improves performance, reducing makespan by up to 23% in standard scheduling scenarios and by up to 38% during rescheduling events, while simultaneously maintaining high system utilization. These findings underscore the effectiveness of integrating simulation with heuristic optimization to provide responsive, real-time control in complex production environments. [ABSTRACT FROM AUTHOR]
Abstract (Arabic): يركز المقال على تطوير إطار عمل هجيني للتخطيط الزمني في ورش العمل (جدولة ورش العمل) يجمع بين التنبؤ والتفاعل لأنظمة التصنيع المرنة (أنظمة التصنيع المرنة) من خلال دمج المحاكاة القائمة على الأحداث المتقطعة (المحاكاة الحدثية المتقطعة) مع خوارزمية جينية (خوارزمية وراثية) كمحسّن. تولّد هذه الطريقة بشكل ديناميكي وتقيّم تسلسلات التوزيع البديلة للتكيف مع الاضطرابات في أرضية الورشة وتغيرات الطلب، مما يحسّن أداء الجدولة من حيث زمن الإنجاز الكلي (مدة التنفيذ)، واستخدام محطات العمل، ومقاييس التأخير. يتضمن الإطار آلية توليد مسارات قائمة على التبديلات (التباديل) ومرشحات تعقيد لإدارة فضاء البحث في عملية التحسين، ويدعم إعادة الجدولة في الوقت الحقيقي من خلال تحديث نموذج المحاكاة بحالات النظام الحالية. تُظهر دراسات الحالة تحسّنات كبيرة تصل إلى 23% في تقليل زمن الإنجاز تحت الجدولة العادية، وتصل إلى 38% أثناء إعادة الجدولة، مما يبرز التطبيق العملي للطريقة في التحكم الاستجابي في بيئات التصنيع المعقدة والقابلة لإعادة التكوين. [Extracted from the article]
Copyright of Jordan Journal of Mechanical & Industrial Engineering is the property of Hashemite University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Towards Predictive and Reactive Job Shop Scheduling: A Hybrid Approach in Flexible Manufacturing Systems.
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  Data: <searchLink fieldCode="JN" term="%22Jordan+Journal+of+Mechanical+%26+Industrial+Engineering%22">Jordan Journal of Mechanical & Industrial Engineering</searchLink>. Mar2026, Vol. 20 Issue 1, p71-86. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Flexible+manufacturing+systems%22">Flexible manufacturing systems</searchLink><br /><searchLink fieldCode="DE" term="%22Discrete+event+simulation%22">Discrete event simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Hybrid+computer+simulation%22">Hybrid computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Scheduling%22">Scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Production+scheduling%22">Production scheduling</searchLink>
– Name: Abstract
  Label: Abstract (English)
  Group: Ab
  Data: In the contemporary manufacturing landscape, unpredictable shop-floor disturbances and shortened product life cycles significantly challenge traditional scheduling methods, often leading to missed due dates and inefficient resource utilization. This study addresses these challenges by proposing a robust predictive--reactive scheduling framework designed for flexible manufacturing systems. The methodology utilizes a hybrid simulation--optimization approach, integrating discrete-event simulation to map real-time system states with a genetic-algorithm-based optimizer to identify high-performing scheduling policies. The framework is uniquely capable of dynamically generating and evaluating alternative dispatch sequences, enabling rapid recovery from operational disruptions such as equipment failure or order changes with minimal deviation from planned workflows. To enhance optimization efficiency, the model incorporates a permutation-based path generator and complexity filters that constrain the search space for the genetic algorithm. Case-study experiments conducted within a reconfigurable manufacturing context demonstrate that the proposed approach significantly improves performance, reducing makespan by up to 23% in standard scheduling scenarios and by up to 38% during rescheduling events, while simultaneously maintaining high system utilization. These findings underscore the effectiveness of integrating simulation with heuristic optimization to provide responsive, real-time control in complex production environments. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label: Abstract (Arabic)
  Group: Ab
  Data: يركز المقال على تطوير إطار عمل هجيني للتخطيط الزمني في ورش العمل (جدولة ورش العمل) يجمع بين التنبؤ والتفاعل لأنظمة التصنيع المرنة (أنظمة التصنيع المرنة) من خلال دمج المحاكاة القائمة على الأحداث المتقطعة (المحاكاة الحدثية المتقطعة) مع خوارزمية جينية (خوارزمية وراثية) كمحسّن. تولّد هذه الطريقة بشكل ديناميكي وتقيّم تسلسلات التوزيع البديلة للتكيف مع الاضطرابات في أرضية الورشة وتغيرات الطلب، مما يحسّن أداء الجدولة من حيث زمن الإنجاز الكلي (مدة التنفيذ)، واستخدام محطات العمل، ومقاييس التأخير. يتضمن الإطار آلية توليد مسارات قائمة على التبديلات (التباديل) ومرشحات تعقيد لإدارة فضاء البحث في عملية التحسين، ويدعم إعادة الجدولة في الوقت الحقيقي من خلال تحديث نموذج المحاكاة بحالات النظام الحالية. تُظهر دراسات الحالة تحسّنات كبيرة تصل إلى 23% في تقليل زمن الإنجاز تحت الجدولة العادية، وتصل إلى 38% أثناء إعادة الجدولة، مما يبرز التطبيق العملي للطريقة في التحكم الاستجابي في بيئات التصنيع المعقدة والقابلة لإعادة التكوين. [Extracted from the article]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Jordan Journal of Mechanical & Industrial Engineering is the property of Hashemite University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.59038/jjmie/200107
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        Text: English
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        PageCount: 16
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      – SubjectFull: Flexible manufacturing systems
        Type: general
      – SubjectFull: Discrete event simulation
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      – SubjectFull: Hybrid computer simulation
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      – SubjectFull: Scheduling
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      – SubjectFull: Genetic algorithms
        Type: general
      – SubjectFull: Production scheduling
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      – TitleFull: Towards Predictive and Reactive Job Shop Scheduling: A Hybrid Approach in Flexible Manufacturing Systems.
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              Text: Mar2026
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