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The pickup and delivery hybrid-operations of AGV conflict-free scheduling problem with time constraint among multi-FMCs

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Abstract

Since much emphasis has been put on the eco-friendly manufacturing process in industries, and the complex changes in market demands, this paper focuses on a green scheduling problem of automated guided vehicles (AGVs) in a flexible manufacturing system (FMS). The studied FMS consists of multi-FMCs (flexible manufacturing cells) which have many material handling needs with time constraints. Distinguished from other AGV scheduling problems in FMS, this paper concentrates on the pickup and delivery operations or even bi-handling requirements of AGVs for FMCs, ignoring the inner production process within them. To solve this problem, a bi-objective mathematical model is built trying to minimize the total tardiness and energy consumption of AGVs simultaneously. Some properties of the problem and a no-collision algorithm are developed for the potential conflicts among AGVs. Due to the NP-hard nature of the proposed problem, a hyper-heuristic (HH) algorithm based on a double deep Q network (DDQN) is introduced, which benefits from the structures of double decision networks and multi-operator. To improve the performance of the proposed algorithm, the experience pool is used to increase the convergence speed and the crowding distance, and the non-dominated sorting strategies are presented to decide the acceptance of the new generation. Besides, in the DDQN, the states and rewards of agents are designed based on the characteristics of the scheduling problem. Finally, many experiments have been conducted and the computational results reveal that the proposed DDQN-HH algorithm outperforms the other two compared algorithms in both the convergence speed and quality of solutions.

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Data availability statement

The authors declare that all data supporting the findings of this study are available within the article and its supplementary information files.

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Authors and Affiliations

  1. School of Mechanical Engineering, Tongji University, Cao’an Road 4800, Mechanical Building A444, Shanghai, 201804, People’s Republic of China

    Binghai Zhou & Yuanrui Lei

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  1. Binghai Zhou
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Contributions

BZ: proposed the research goals and aims. Verified the overall results, experiments, and other outputs. Provided the computing resources and analysis tools. Reviewed the initial draft and revised the manuscript. In charge of acquisition of the financial support for the project leading to this publication. YL: developed and designed the mathematical model and methodology. Performed software development and experiments. Conducted the statistical analysis. Wrote the initial draft and revised the manuscript.

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Correspondence to Binghai Zhou.

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Appendix

Appendix

Abbreviation

Definition

AGV

Automated guided vehicle

FMS

Flexible manufacturing system

FMC

Flexible manufacturing cell

DDQN

Double deep Q network

DDQN-HH

Double deep Q network-hyper heuristic

HH

Hyper heuristic

CNC

Computer numerical control

NP

Non-deterministic polynomial

ML

Machine learning

RL

Reinforcement learning

LLH

Low-level heuristic

I/O

Input and output

FILO

First in last out

JIT

Just in time

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Zhou, B., Lei, Y. The pickup and delivery hybrid-operations of AGV conflict-free scheduling problem with time constraint among multi-FMCs. Neural Comput & Applic 35, 23125–23151 (2023). https://doi.org/10.1007/s00521-023-08897-z

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