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author:

Xin, J. (Xin, J..) [1] | Liu, C. (Liu, C..) [2] | D'ariano, A. (D'ariano, A..) [3] | Qiang, Liu, S. (Qiang, Liu, S..) [4] | Liang, J. (Liang, J..) [5]

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Abstract:

In the stockyard of dry bulk materials such as coal and iron ore, multiple stacker-reclaimers operate collaboratively to enhance stockyard productivity. However, effectively planning the routes for these interconnected machines presents a significant challenge. We propose a new modeling framework for this conflict-free routing problem in which the reclaiming process is modeled in a so-called time-space network (TSN) framework. The formulated optimization problem is mixed integer programming (MIP), which has been proven NP-hard. To address its computational efficiency, we develop a two-level metaheuristic algorithm to simplify the encoding complexity of the original problem. In the developed two-level algorithm, a task priority ordering candidate is listed at the top level, while the detailed conflict-free routes are constructed at the bottom level using an insertion-based conflict-free reclaiming and customized route improvement. The developed metaheuristic is tested on a large number of instances in comparison with the Gurobi solver and three commonly used methods for such a routing problem. The experimental results show that the proposed algorithm outperforms the other four methods regarding the solution quality and the computation time.  © 2004-2012 IEEE.

Keyword:

Dry bulk stockyard reclaimer scheduling time-space network model two-level metaheuristic

Community:

  • [ 1 ] [Xin J.]Zhengzhou University, School of Electrical and Information Engineering, Zhengzhou, 450001, China
  • [ 2 ] [Xin J.]State Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang, 471039, China
  • [ 3 ] [Liu C.]Zhengzhou University, School of Electrical and Information Engineering, Zhengzhou, 450001, China
  • [ 4 ] [D'ariano A.]Roma Tre University, Department of Civil, Computer Science and Aeronautical Technologies Engineering, Rome, 00146, Italy
  • [ 5 ] [Qiang Liu S.]Fuzhou University, School of Management and Economics, Fuzhou, 350108, China
  • [ 6 ] [Liang J.]Zhengzhou University, School of Electrical and Information Engineering, Zhengzhou, 450001, China
  • [ 7 ] [Liang J.]State Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang, 471039, China

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IEEE Transactions on Automation Science and Engineering

ISSN: 1545-5955

Year: 2025

Volume: 22

Page: 7335-7348

5 . 9 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 1

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