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The dynamic shortest path problem with time-dependent stochastic disruptions
Institution:1. School of Industrial Engineering, Eindhoven University of Technology, Eindhoven, Netherlands;2. Department of Industrial Engineering, Tsinghua University, Beijing, China;3. Panalpina Centre for Manufacturing and Logistics Research, Cardiff Business School, Cardiff University, Cardiff, United Kingdom;1. School of Computer and Communication Engineering, Tianjin University of Technology, Tianjin, China;2. State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China;3. School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China;1. Department of Transportation Planning, Faculty of Civil Engineering, Iran University of Science Technology, Tehran, Iran;2. Department of Computer Engineering, Sungkyunkwan University, Suwon 440746, Republic of Korea;1. Business School, Sichuan University, Chengdu, China;2. NHH Norwegian School of Economics, Bergen, Norway;3. SINTEF Technology and Society, Trondheim, Norway
Abstract:The dynamic shortest path problem with time-dependent stochastic disruptions consists of finding a route with a minimum expected travel time from an origin to a destination using both historical and real-time information. The problem is formulated as a discrete time finite horizon Markov decision process and it is solved by a hybrid Approximate Dynamic Programming (ADP) algorithm with a clustering approach using a deterministic lookahead policy and value function approximation. The algorithm is tested on a number of network configurations which represent different network sizes and disruption levels. Computational results reveal that the proposed hybrid ADP algorithm provides high quality solutions with a reduced computational effort.
Keywords:Dynamic shortest path problem  Approximate dynamic programming  Time-dependent disruption  Lookahead policy  Value function approximation
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