An Analytic Model for Design of a Multivehicle Automated Guided Vehicle System

We consider the problem of designing a multivehicle automated guided vehicle system (AGVS) to supplement an existing nonautomated material handling system. The AGVS consists of a pool of vehicles that deliver raw components from a central storage area to workcenters throughout the factor floor. The...

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Vydáno v:Management science Ročník 39; číslo 12; s. 1477 - 1489
Hlavní autoři: Johnson, M. Eric, Brandeau, Margaret L
Médium: Journal Article
Jazyk:angličtina
Vydáno: Linthicum, MD INFORMS 01.12.1993
Institute of Management Sciences
Institute for Operations Research and the Management Sciences
Edice:Management Science
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ISSN:0025-1909, 1526-5501
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Abstract We consider the problem of designing a multivehicle automated guided vehicle system (AGVS) to supplement an existing nonautomated material handling system. The AGVS consists of a pool of vehicles that deliver raw components from a central storage area to workcenters throughout the factor floor. The objective is to determine which workcenters warrant automated component delivery and the number of vehicles required to service those workcenters, to maximize the benefit of the AGVS, subject to a constraint that the average waiting time for material transport in the system not exceed a predefined limit. The pool of vehicles is modeled as an M / G / c queuing system and the design model is formulated as a binary integer program with nonlinear waiting time constraints, which are expressed by approximate queueing formula. We develop two different implicit enumeration algorithms to exactly solve the analytical model. We illustrate our model with an example of an actual AGVS design problem at Hewlett-Packard, and we present computational experience for other example design problems. We show how sensitivity analysis can be used to ensure that the analytical model yields an optimal solution to the design problem.
AbstractList We consider the problem of designing a multivehicle automated guided vehicle system (AGVS) to supplement an existing nonautomated material handling system. The AGVS consists of a pool of vehicles that deliver raw components from a central storage area to workcenters throughout the factor floor. The objective is to determine which workcenters warrant automated component delivery and the number of vehicles required to service those workcenters, to maximize the benefit of the AGVS, subject to a constraint that the average waiting time for material transport in the system not exceed a predefined limit. The pool of vehicles is modeled as an M/G/c queuing system and the design model is formulated as a binary integer program with nonlinear waiting time constraints, which are expressed by approximate queueing formula. We develop two different implicit enumeration algorithms to exactly solve the analytical model. We illustrate our model with an example of an actual AGVS design problem at Hewlett-Packard, and we present computational experience for other example design problems. We show how sensitivity analysis can be used to ensure that the analytical model yields an optimal solution to the design problem.
We consider the problem of designing a multivehicle automated guided vehicle system (AGVS) to supplement an existing nonautomated material handling system. The AGVS consists of a pool of vehicles that deliver raw components from a central storage area to workcenters throughout the factor floor. The objective is to determine which workcenters warrant automated component delivery and the number of vehicles required to service those workcenters, to maximize the benefit of the AGVS, subject to a constraint that the average waiting time for material transport in the system not exceed a predefined limit. The pool of vehicles is modeled as an M / G / c queuing system and the design model is formulated as a binary integer program with nonlinear waiting time constraints, which are expressed by approximate queueing formula. We develop two different implicit enumeration algorithms to exactly solve the analytical model. We illustrate our model with an example of an actual AGVS design problem at Hewlett-Packard, and we present computational experience for other example design problems. We show how sensitivity analysis can be used to ensure that the analytical model yields an optimal solution to the design problem.
The problem of designing a multivehicle automated guided vehicle system (AGVS) to supplement an existing nonautomated material handling system is considered. The AGVS consists of a pool of vehicles that deliver raw components from a central storage area to workcenters throughout the factor floor. The objective is to determine which workcenters warrant automated component delivery and the number of vehicles required to service those workcenters, to maximize the benefit of the AGVS, subject to a constraint that the average waiting time for material transport in the system not exceed a predefined limit. The pool of vehicles is modeled as a M/G/c queuing system and the design model is formulated as a binary integer program with nonlinear waiting time constraints, which are expressed by approximate queuing formula. Two different implicit enumeration algorithms are developed to exactly solve the analytical model. The model is illustrated with an example of an actual AGVS design problem at Hewlett-Packard, and computational experience is presented for other example design problems. It is also shown how sensitivity analysis can be used to ensure that the analytical model yields an optimal solution to the design problem.
Author Brandeau, Margaret L
Johnson, M. Eric
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Issue 12
Keywords Integer programming
Automation
Sensitivity analysis
Branch and bound method
Implicit enumeration method
Manufacturing
Automated guided vehicle
Transport
Queue
Handling
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Snippet We consider the problem of designing a multivehicle automated guided vehicle system (AGVS) to supplement an existing nonautomated material handling system. The...
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SubjectTerms AGVS
Algorithms
Analysis
Analytical models
Applied sciences
Approximation
automated systems
Automation
Computer science; control theory; systems
Constraints
Control theory. Systems
Design analysis
Enumeration
Exact sciences and technology
Intelligent vehicles
Manufacturing
Materials handling
Mathematical models
Motor vehicle traffic
network models
Optimal solutions
Process control. Computer integrated manufacturing
Queueing
Queuing theory
Sensitivity analysis
Storage
Systems design
Transport
Transportation
Travel time
Vehicles
Title An Analytic Model for Design of a Multivehicle Automated Guided Vehicle System
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