Simultaneous Dispatching and Scheduling of Multi-Load AGVs in FMS-A Simulation Study

Chawla, V. K.; Chanda, Arindam Kumar; Angra, Surjit; Rani, Sushma

doi:10.1016/j.matpr.2018.10.339

Cited by 11 publications

(5 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Simulation modeling finds a wide range application and consequently, several studies based on it have been conducted by researchers for examining and improving performance of the FMSs. For example, Chawla et al, (2018) performed a simulation based investigation to determine optimal utilization of the AGVs [26]. Amoako-Gyampah & Meredith, (1996) conducted a simulation based study and suggested different heuristics for tool allocations in FMS [27].…”

Section: Simulation Modellingmentioning

confidence: 99%

A Novel Framework Based on Integration of Simulation Modelling and Mcdm Methods for Solving Fms Scheduling Problems

Ahmad,

A. Khan,

Ali

et al. 2023

IJCAI

View full text Add to dashboard Cite

Scheduling in Flexible Manufacturing Systems (FMSs) is an important area of research as it significantly affects performance of the systems. In scheduling problems, determination of an appropriate order for jobs to be processed on a machine is a difficult task and to solve such problems, job priority rules (JPRs) are used. Several JPRs have been developed with an aim to obtain better performance, measured in terms of one or more scheduling performance measures (SPMs). However, selection of an appropriate rule is still an area of research as no single rule provides better results for all SPMs considered simultaneously. This work proposes a framework which is based on an integration of simulation and multi criteria decision making (MCDM) methods for the selection of an appropriate JPR yielding optimum results for multiple SPMs taken together. The proposed framework includes development of a simulation model to collect values of the SPMs corresponding to different JPRs. Further, five MCDM methods have been used to determine rank of the JPRs. Since different MCDM methods produce different ranking result therefore, the final rank of the JPRs has been determined by comparing the rank derived from these methods using membership degree method. To exemplify the probable application of the proposed framework, it has been implemented on a specific FMS taken from the literature in order to select the best JPR.Povzetek: Razvit je okvir za reševanje problemov razporejanja v fleksibilnih proizvodnih sistemih, ki združuje simulacijsko modeliranje in metode MCDM.

show abstract

Section: Simulation Modellingmentioning

confidence: 99%

A Novel Framework Based on Integration of Simulation Modelling and Mcdm Methods for Solving Fms Scheduling Problems

Ahmad,

A. Khan,

Ali

et al. 2023

IJCAI

View full text Add to dashboard Cite

show abstract

“…The article highlighted the importance of selecting an appropriate number of AGVs through experiments. Chawla et al [90] found that AGV speed and AGVs fleet size had a significant role in the increase or decrease of throughput of the FMS. Wu et al [91] discussed the interaction between the number of AGVs and the load capacity of AGVs in the manufacturing system.…”

Section: The Number Of Agvs In the Systemmentioning

confidence: 99%

Analysis of Multi-AGVs Management System and Key Issues: A Review

Lu¹,

Guo²,

Song³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

View full text Add to dashboard Cite

Multiple Automatic Guided Vehicle (multi-AGVs) management systems provide an effective solution to ensuring stable operations of multi-AGVs in the same scenario, such as flexible manufacturing systems, warehouses, container terminals, etc. This type of systems need to balance the relationship among the resources of the system and solve the problems existing in the operation to make the system in line with the requirement of the administrator. The multi-AGVs management problem is a multi-objective, multi-constraint combinatorial optimization problem, which depends on the types of application scenarios. This article classifies and compares the research papers on multi-AGVs management in detail. Firstly, according to the different dimensions of the problem, the multi-AGVs management system is analyzed from three perspectives, namely, 1) task dimensiondispatch, 2) spatial dimension-path, and 3) time dimension-scheduling. The detailed comparison between the three dimensions and their respective solutions are discussed in detail as well. Secondly, according to their utility, the multi-AGVs management problems are divided into three categories: 1) cost reduction, resource-oriented, 2) efficiency improvement, problem-oriented, 3) personalized demand, goal-oriented. The algorithm and methods of the different utility-oriented are analyzed and discussed. The related literature is summarized and corresponds to the composition of the multi-AGVs management system and the multi-AGVs management problems. Finally, according to the literature review, suggestions are made for further research.

show abstract

“…The constraint condition (5) means that the number of orders allocated to each batch does not exceed the specified maximum quantity. The constraint condition (6) means that if any order in batch k contains product t. The batch constraint condition (7) means that if batch k contains commodity t, the shelf containing commodity t needs to be transported when picking this batch. Constraint conditions (8-10) represent the value constraints of decision variables.…”

Section: Integer Programming Model Of Agv Order Batchingmentioning

confidence: 99%

“…When multiple AGVs are working at the same time, how to effectively avoid conflicts between AGVs is particularly important. For the multi-AGV scheduling problem, Chawlal et al [7] compared five dynamic scheduling rules. Fanjupeyro et al [8] proposed precise algorithm, because Multi-AGV scheduling problem is equivalent to Unrelated Parallel Machine Scheduling Problem (UPMSP).…”

Section: Introductionmentioning

confidence: 99%

Research on Improving E-commerce Logistics Service Customer Satisfaction Through Application of AGV in Intelligent Warehouse

Xiao

Ahmad

Mamun

2021

Proceedings of International Conference on Emerging Technologies and Intelligent Systems

View full text Add to dashboard Cite

In the process of e-commerce logistics operation, warehousing order picking speed directly affects customer satisfaction. With the surge of orders, e-commerce intelligent warehouses apply automatic guided vehicles (AGV) to improve the efficiency of order processing and increase customer satisfaction. This paper proposes using simulation to optimize the AGV road network through building an intelligent warehouse simulation model in Anylogic simulation software to collect data of AGV operation under different road networks, and optimize the road network by changing the warehouse layout. Moreover, in order to cope with the rapid increase in the number of orders, this paper builds an AGV order batching integer planning model. Through applying the optimized intelligent warehousing AGV road network, combined with the integer programming model and algorithm for order batching, e-commerce intelligent warehouse can effectively increase the efficiency of AGV order picking, reduce AGV operating costs, therefore improve e-commerce logistics service quality and customer satisfaction.

show abstract

Simultaneous Dispatching and Scheduling of Multi-Load AGVs in FMS-A Simulation Study

Cited by 11 publications

References 19 publications

A Novel Framework Based on Integration of Simulation Modelling and Mcdm Methods for Solving Fms Scheduling Problems

A Novel Framework Based on Integration of Simulation Modelling and Mcdm Methods for Solving Fms Scheduling Problems

Analysis of Multi-AGVs Management System and Key Issues: A Review

Research on Improving E-commerce Logistics Service Customer Satisfaction Through Application of AGV in Intelligent Warehouse

Contact Info

Product

Resources

About