Multiagent scheduling method with earliness and tardiness objectives in flexible job shops

Area of Science:

• Operations Research
• Industrial Engineering
• Artificial Intelligence

Background:

• Flexible job-shop scheduling problems (FJSP) present significant complexity due to overlapping machine capacities, challenging traditional scheduling methods.
• Existing classical scheduling approaches are often inadequate for addressing the intricacies of modern flexible manufacturing systems.

Purpose of the Study:

• To propose a novel multiagent scheduling method for flexible job-shop environments.
• To incorporate job earliness and tardiness objectives, aligning with the just-in-time (JIT) production philosophy.
• To develop an efficient job-routing and sequencing mechanism for improved scheduling performance.

Main Methods:

• A multiagent scheduling approach was developed, integrating job earliness and tardiness objectives.
• A new job-routing mechanism was introduced, differentiating jobs based on remaining operations.
• Two heuristic algorithms were designed for job sequencing to manage early completions.

Main Results:

• The proposed multiagent scheduling method demonstrated superior performance compared to existing literature methods.
• The method effectively addresses job earliness and tardiness objectives within a flexible job-shop setting.
• Computational experiments confirmed the method's efficiency, with scheduling times under 1.5 minutes for over 2000 jobs.

Conclusions:

• The developed multiagent scheduling method offers a significant advancement for flexible job-shop scheduling.
• The approach aligns with just-in-time principles and provides a fast, effective solution for complex scheduling scenarios.
• This method presents a viable and efficient alternative for industrial applications requiring optimized job-shop scheduling.