Application of Layered Coding Genetic Algorithm in Optimization of Unequal Area Production Facilities Layout.

Area of Science:

• Operations Research
• Industrial Engineering
• Computational Optimization

Background:

• The unequal area facilities layout problem (UA-FLP) is critical for enterprise construction, reconstruction, and expansion.
• Facilities layout significantly impacts production system operational performance.
• Optimal UA-FLP solutions are essential for efficient plant design.

Purpose of the Study:

• To develop an effective algorithm for solving the UA-FLP.
• To optimize facility layout considering area, aspect ratio, logistics costs, and adjacency relations.
• To provide decision support for rapid and optimal multifacility layout.

Main Methods:

• Utilized a slicing tree method to partition layout space into regions for each facility.
• Developed a genetic algorithm with layered coding to represent the slicing process.
• Formulated a goal function incorporating production logistics cost and facility adjacency.

Main Results:

• The proposed genetic algorithm successfully obtained optimal solutions for the UA-FLP.
• The slicing tree approach effectively divided the layout space.
• Validation on known problems confirmed the algorithm's feasibility and effectiveness.

Conclusions:

• The developed genetic algorithm provides a viable approach for solving the UA-FLP.
• The method offers decision support for efficient and rapid multifacility layout design.
• This approach enhances the rationality of facilities layout in industrial settings.