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A new approach for bin packing problem using knowledge reuse and improved heuristic.

Jie Fang1,2,3, Xubing Chen4,5, Yunqing Rao6

  • 1Hubei Provincial Key Laboratory of Chemical Equipment Intensification and Intrinsic Safety, Wuhan Institute of Technology, Wuhan, 430205, P. R. China.

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Summary
This summary is machine-generated.

This study introduces a new algorithm for the 2D irregular packing problem, enhancing knowledge reuse for efficiency. The KRIH algorithm offers robust solutions and performs competitively with existing methods.

Keywords:
Heuristic algorithmsIrregular pieceKnowledge reuseKnowledge transferPacking problem

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Area of Science:

  • Operations Research
  • Computer Science
  • Artificial Intelligence

Background:

  • The two-dimensional (2D) irregular packing problem is NP-complete, impacting industries like apparel and metal fabrication.
  • Existing hybrid heuristic and meta-heuristic algorithms are complex and time-consuming.

Purpose of the Study:

  • To develop an efficient and robust algorithm for 2D irregular packing.
  • To leverage knowledge reuse from similar packing tasks.
  • To improve upon classical packing algorithms.

Main Methods:

  • Utilized a twin neural network for similarity measurement between packing tasks.
  • Implemented a transfer operator for knowledge reuse.
  • Enhanced the bottom-left algorithm for piece placement.
  • Developed the Knowledge Reuse and Improved Heuristic (KRIH) algorithm.

Main Results:

  • The KRIH algorithm demonstrated good robustness in computational experiments.
  • KRIH achieved equal or better results than classical algorithms on 16 instances.
  • The algorithm operated within a relatively short time frame.

Conclusions:

  • The KRIH algorithm effectively reuses packing knowledge, improving efficiency.
  • The proposed method shows significant application potential for 2D irregular packing problems.
  • KRIH offers a competitive alternative to existing packing solutions.