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Migration

Migration

Migration is long-range, seasonal movement from one region or habitat to another. This common strategy, carried out by many different organisms around the world, is an adaptive response that typically corresponds to changes in an organism’s environment, like resource availability or climate. Migrations can involve huge groups of thousands of animals as well as single individuals traveling alone and can range from thousands of kilometers to just a few hundred meters.

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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

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Virtual Simulation-Based Optimization for Assembly Flow Shop Scheduling Using Migratory Bird Algorithm.

Wen-Bin Zhao¹, Jun-Han Hu¹, Zi-Qiao Tang²

¹College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.

Biomimetics (Basel, Switzerland)

|September 27, 2024

Summary

This summary is machine-generated.

This study introduces an efficient migratory bird optimization algorithm for factory scheduling. It improves production scheduling and forecasting accuracy in flexible manufacturing, minimizing completion times.

Keywords:

bionic optimization algorithm hybrid assembly flow shop migratory bird optimization algorithm multi-mold constraint virtual simulation

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Area of Science:

Industrial Engineering
Operations Research
Computational Intelligence

Background:

Industrial informatization drives adoption of virtual simulation for real-time data capture and digital model construction.
Bionic optimization algorithms show promise for enhancing efficiency in manufacturing scheduling and operations.
Flexible and mixed-flow production modes require advanced scheduling solutions for improved accuracy.

Purpose of the Study:

To develop an efficient migratory bird optimization algorithm for production scheduling in assembly shops with mold constraints.
To minimize the maximum completion time for batch flow mixed assembly flow shop scheduling problems.
To integrate a virtual simulation framework and variable batch partitioning strategies.

Main Methods:

A two-stage encoding mechanism for batch partitioning and sequencing tailored to production stages.
Optimization strategies for batch partitioning and sequencing, including adaptive neighborhood structure adjustment.
A competition mechanism to enhance the algorithm's optimization efficiency.

Main Results:

The migratory bird optimization algorithm effectively addresses production scheduling challenges.
Variable batch partitioning strategies demonstrated a 5-6% improvement over equal batch strategies.
Simulation experiments confirmed the algorithm's robustness across various scales and parameters.

Conclusions:

The proposed algorithm and variable batch partitioning strategy enhance production scheduling efficiency.
Virtual simulation combined with bionic optimization offers a powerful approach for modern manufacturing.
The study provides a robust solution for complex assembly shop scheduling problems.