Revised electromagnetism-like mechanism for flow path design of unidirectional AGV systems

Guan, Xianping; Duan, Xianzhong; Li, Jun

doi:10.1080/00207540903490155

Cited by 22 publications

(10 citation statements)

References 23 publications

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“…e integrated design method proposed in this paper is compared with the traditional stepwise design methods, which can be implemented as follows: firstly, the technological route information is converted into the loaded flow matrix among all loading and unloading points (Table 5). Secondly, with the objective of minimizing both loaded and empty travel distance, the method proposed by GUAN and DAI [8] is used to design the UGN. e results obtained by the method is the optimal UGN code [111111100], which corresponds to the UGN shown in Figure 3.…”

Section: Task Sequence Elitism Strategymentioning

confidence: 99%

“…Besides, the algorithm has the comparatively strong dependence on the initial status, thereby being prone to fall into the local optimum. Guan et al [8] proposed an improved electromagnetism-like mechanism algorithm to minimize both loaded and empty travel distance. Functionally similar approaches also include the genetic algorithm [9,10] and the met heuristics algorithm [11].…”

Section: Introductionmentioning

confidence: 99%

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A CEGA-Based Optimization Approach for Integrated Designing of a Unidirectional Guide-Path Network and Scheduling of AGVs

Xiao

Zeng

et al. 2020

Mathematical Problems in Engineering

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In the current industrial fields, automatic guided vehicles (AGVs) are widely employed to constitute the flexible manufacturing system (FMS), owing to their great advantages of routing flexibility and high efficiency. However, one main challenge lies in the coupling process of the design problem of the unidirectional guide-path network (UGN) and the task scheduling problem of AGVs. To reduce the complexity, most pertinent literatures only handle these problems one by one, based on the stepwise design methods, thereby neglecting the constraint conditions and the optimization objectives caused by the FMS environment. The motivation of the paper is to bring the coupling factors into the integrated design and solution process. Firstly, an integrated design model of designing UGN and scheduling AGVs simultaneously is proposed, with the objective of minimizing the makespan (i.e., the maximum completion time of all handling tasks), in the consideration of the practical constraints, e.g., the job handling and processing sequence constraints and the AGV number constraint. Secondly, a dual-population collaborative evolutionary genetic algorithm (CEGA) is developed to solve the problems of designing and scheduling in a parallel way. The solutions of the integrated model, i.e., the potential strongly connected UGN and the feasible processing and handling sequence, are, respectively, coded as two different subpopulations with independent and concurrent evolution processes. The neighbourhood search operation, the niche technique, and the elitism strategy are combined to improve the convergence speed and maintain the population diversity. The experimental results show that the integrated design model can formulate the problem more accurately, and the CEGA algorithm is computationally efficient with high solution quality.

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Section: Task Sequence Elitism Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A CEGA-Based Optimization Approach for Integrated Designing of a Unidirectional Guide-Path Network and Scheduling of AGVs

Xiao

Zeng

et al. 2020

Mathematical Problems in Engineering

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“…EMO algorithm has been applied to capacitated VRP by Yurtkuran and Emel (). EMO algorithm has also found applications in several other domains such as fuzzy systems (Birbil & Feyzioglu, ; Lee, Kuo, Chang, Chien, & Chang, ; Wu, Yang, & Hung, ), neural network (Wang, Gao, & Zhang, ; Wu, Zhang, Gao, & Li, ), multi‐objective inventory control (Tsou & Kao, ), antenna application (Lee & Jhang, ), robotics application (Santos et al, ), PID (proportional‐integral‐differential) controller (Lee & Chang, ), networking (Tsai, Hung, & Lee, ), flow path designing (Guan, Dai, & Li, ), feature selection (Su & Lin, ), and tool path planning (Kuo, Chu, Li, Li, & Gao, ). Bonyadi and Li () proposed a discrete EMO to solve the MKP problem, where GA operators (Reyes, Morell, & Ventura, ; Menendez, Barrero, & Camacho, ) are utilized to work in discrete spaces.…”

Section: Electromagnetism Optimizationmentioning

confidence: 99%

Physics‐based search and optimization: Inspirations from nature

Siddique

Adeli

2016

Expert Systems

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“…Sinriech and Tanchoco (1991), Kaspi et al (2002), Lim et al (2002a), Lim et al (2002b), Guan et al (2011), andSinggih andKim (2015) studied the empty travels of transporters.…”

Section: Flow Path Design For Automated Transport Systems In Containementioning

confidence: 99%

Flow Path Design for Automated Transport Systems in Container Terminals Considering Traffic Congestion

Singgih¹,

Hong²,

Kim³

2016

Industrial Engineering and Management Systems

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A design method of the network for automated transporters mounted on rails is addressed for automated container terminals. In the network design, the flow directions of some path segments as well as routes of transporters for each flow requirement must be determined, while the total transportation and waiting times are minimized. This study considers, for the design of the network, the waiting times of the transporters during the travel on path segments, intersections, transfer points below the quay crane (QC), and transfer points at the storage yard. An algorithm, which is the combination of a modified Dijkstra's algorithm for finding the shortest time path and a queuing theory for calculating the waiting times during the travel, is proposed. The proposed algorithm can solve the problem in a short time, which can be used in practice. Numerical experiments showed that the proposed algorithm gives solutions better than several simple rules. It was also shown that the proposed algorithm provides satisfactory solutions in a reasonable time with only average 7.22% gap in its travel time from those by a genetic algorithm which needs too long computational time. The performance of the algorithm is tested and analyzed for various parameters.

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Revised electromagnetism-like mechanism for flow path design of unidirectional AGV systems

Cited by 22 publications

References 23 publications

A CEGA-Based Optimization Approach for Integrated Designing of a Unidirectional Guide-Path Network and Scheduling of AGVs

A CEGA-Based Optimization Approach for Integrated Designing of a Unidirectional Guide-Path Network and Scheduling of AGVs

Physics‐based search and optimization: Inspirations from nature

Flow Path Design for Automated Transport Systems in Container Terminals Considering Traffic Congestion

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