A Decision Framework for Automatic Guided Vehicle Routing Problem with Traffic Congestions
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A Decision Framework for Automatic Guided Vehicle Routing Problem with Traffic Congestions Lu Zhen1 · Yi-Wei Wu1 · Si Zhang1
· Qiu-Ji Sun1 · Qi Yue1
Received: 22 May 2018 / Revised: 20 July 2018 / Accepted: 27 August 2018 / Published online: 10 October 2018 © Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag GmbH Germany, part of Springer Nature 2018
Abstract Automatic guided vehicles are widely used in various types of warehouses including the automated container terminals. This paper provides a decision framework for port managers to design and schedule automatic guided vehicle routing plans under timevarying traffic conditions. A large number of computational experiments on a grid graph are conducted to validate the efficiency of the proposed decision framework. We also proposed one efficient queueing rule in automatic guided vehicle routing scheduling. Although the complexity of the problem is high, computational results show that our proposed decision framework can provide high quality solutions within a relatively short computation time. Keywords Automatic guided vehicle · Multiple vehicle routing · Traffic congestions · Decision framework Mathematics Subject Classification 90B06 · 90B20 · 90C90
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Si Zhang [email protected] Lu Zhen [email protected] Yi-Wei Wu [email protected] Qiu-Ji Sun [email protected] Qi Yue [email protected]
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School of Management, Shanghai University, Shanghai 200444, China
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L. Zhen et al.
1 Introduction Due to the rapid development of global economy, container transportation plays more and more important role in world trade. According to the 2017 maritime transportation review published by the United Nations Conference on Track and Development, total volume of world containers in seaborne trade is 1 720 million tons in 2016. The huge number of containers brings an operational challenge to port owners and shipping companies. Therefore, the efficient port management has become a vital issue in port operations. Typical operations in a container terminal usually contain berth assignment, quay crane allocation, yard storage area design and allocation, and so on [1]. Among these operations, the automatic guided vehicle routing problem (AGVRP) in a container terminal has become an important problem restricting the efficiency of port container handling as Automated Guided Vehicles (AGVs) are gradually widely used in the automated container terminals. Under such conditions, AGVRP is crucial for sea transportation development. AGV is a driverless material handling system used for horizontal movement of materials [2]. AGVRP is similar to the traditional vehicle routing problem (VRP), but AGVRP is more difficult and complex to study because of its unique characteristics. The traditional VRP usually studies the path networks of cities. In this case, some factors affecting the load capacity of a path, such as vehicle collisions and traffic congestions, are insignificant when compared with the travel distance.
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