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Genetic Programming with Delayed Routing for Multiobjective Dynamic Flexible Job Shop Scheduling.

Binzi Xu1, Yi Mei2, Yan Wang3

  • 1School of Electrical Engineering, Anhui Polytechnic University, Wuhu, 241000, PR China School of IoT and Engineering, Jiangnan University, Wuxi, 214122, PR China School of Engineering and Computer Science, Victoria University of Wellington, Wellington 6140, New Zealand 7151905016@vip.jiangnan.edu.cn.

Evolutionary Computation
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Summary
This summary is machine-generated.

This study introduces a novel approach for Dynamic Flexible Job Shop Scheduling (DFJSS) by delaying routing decisions. This Genetic Programming Hyper-Heuristic with Delayed Routing (GPHH-DR) method significantly improves scheduling efficiency.

Keywords:
Dynamic flexible job shop schedulingdelayed routingdispatching rule discoveryenergy efficiency.genetic programming

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Area of Science:

  • Operations Research
  • Artificial Intelligence
  • Manufacturing Systems

Background:

  • Dynamic Flexible Job Shop Scheduling (DFJSS) presents complex, multi-objective challenges.
  • Existing Genetic Programming Hyper-Heuristic (GPHH) methods for DFJSS have limitations in dynamic environments due to immediate decision-making.

Purpose of the Study:

  • To propose a novel heuristic template for DFJSS that delays routing decisions.
  • To enhance the responsiveness and accuracy of scheduling decisions in dynamic environments.

Main Methods:

  • Developed a new heuristic template that postpones routing decisions until the latest possible moment.
  • Proposed three distinct delayed routing strategies.
  • Utilized GPHH to automatically evolve dispatching rules within the heuristic template.
  • Evaluated the GPHH with Delayed Routing (GPHH-DR) on a multi-objective DFJSS problem optimizing energy efficiency and mean tardiness.

Main Results:

  • The GPHH-DR approach demonstrated significant performance improvements over state-of-the-art GPHH methods.
  • Experimental results validated the effectiveness of delaying routing decisions in DFJSS.

Conclusions:

  • Delaying routing decisions in DFJSS is crucial for optimizing scheduling performance.
  • The proposed GPHH-DR method offers a superior solution for dynamic and multi-objective job shop scheduling problems.