Route Construction Algorithms for Time Dependent Vehicle Routing Problem

Duan, Zhengyu; Yang, Dongyuan; Sun, Wei; Wang, Shang

doi:10.1061/41139(387)484

Cited by 4 publications

(6 citation statements)

References 5 publications

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“…In equation (26), n is the number of customer nodes, ST(0) is the total schedule time of the initial solution.…”

Section: (B) Initial Pheromonementioning

confidence: 99%

“…Generate the initial solution by an efficient route construction algorithm named nearest-neighbor algorithm based on minimum cost (NNC). 26 2. Design a new customer node choice method by the transition probability considering both travel time and time windows.…”

Section: Aco Algorithmmentioning

confidence: 99%

“…(a) Initial solution NNC is an efficient route construction algorithm for TDVRP, 26 which is extended from Solomon's 27 nearest-neighbor (NN) algorithm for VRP.…”

Section: Procedures Of Aco Algorithmmentioning

confidence: 99%

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Stochastic time-dependent vehicle routing problem: Mathematical models and ant colony algorithm

Duan

Sun

et al. 2015

Advances in Mechanical Engineering

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This article addresses the stochastic time-dependent vehicle routing problem. Two mathematical models named robust optimal schedule time model and minimum expected schedule time model are proposed for stochastic time-dependent vehicle routing problem, which can guarantee delivery within the time windows of customers. The robust optimal schedule time model only requires the variation range of link travel time, which can be conveniently derived from historical traffic data. In addition, the robust optimal schedule time model based on robust optimization method can be converted into a time-dependent vehicle routing problem. Moreover, an ant colony optimization algorithm is designed to solve stochastic time-dependent vehicle routing problem. As the improvements in initial solution and transition probability, ant colony optimization algorithm has a good performance in convergence. Through computational instances and Monte Carlo simulation tests, robust optimal schedule time model is proved to be better than minimum expected schedule time model in computational efficiency and coping with the travel time fluctuations. Therefore, robust optimal schedule time model is applicable in real road network.

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“…In equation (26), n is the number of customer nodes, ST(0) is the total schedule time of the initial solution.…”

Section: (B) Initial Pheromonementioning

confidence: 99%

Section: Aco Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Stochastic time-dependent vehicle routing problem: Mathematical models and ant colony algorithm

Duan

Sun

et al. 2015

Advances in Mechanical Engineering

Self Cite

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show abstract

“…Duan et al [18] extended the route construction algorithm, namely, NNC (nearest neighbor algorithm base on minimum cost) algorithm for solving the TDVRP in extended Solomon instances. Considering computing time and solution quality synthetically, he proved that the extended NNC algorithm had a better performance compared with some other existing algorithms.…”

Section: Algorithm For Stdvrptwmentioning

confidence: 99%

“…Constraint (17) is added for route continuity. Constraints (18) and (19) are added as time window constraints.…”

Section: Model For Stdvrptwmentioning

confidence: 99%

Urban Freight Management with Stochastic Time-Dependent Travel Times and Application to Large-Scale Transportation Networks

Sun

Duan

Yang

2015

Discrete Dynamics in Nature and Society

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This paper addressed the vehicle routing problem (VRP) in large-scale urban transportation networks with stochastic timedependent (STD) travel times. The subproblem which is how to find the optimal path connecting any pair of customer nodes in a STD network was solved through a robust approach without requiring the probability distributions of link travel times. Based on that, the proposed STD-VRP model can be converted into solving a normal time-dependent VRP (TD-VRP), and algorithms for such TD-VRPs can also be introduced to obtain the solution. Numerical experiments were conducted to address STD-VRPTW of practical sizes on a real world urban network, demonstrated here on the road network of Shenzhen, China. The stochastic timedependent link travel times of the network were calibrated by historical floating car data. A route construction algorithm was applied to solve the STD problem in 4 delivery scenarios efficiently. The computational results showed that the proposed STD-VRPTW model can improve the level of customer service by satisfying the time-window constraint under any circumstances. The improvement can be very significant especially for large-scale network delivery tasks with no more increase in cost and environmental impacts.

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An adaptive parallel route construction heuristic for the vehicle routing problem with time windows constraints

Pang

2011

Expert Systems with Applications

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Route Construction Algorithms for Time Dependent Vehicle Routing Problem

Cited by 4 publications

References 5 publications

Stochastic time-dependent vehicle routing problem: Mathematical models and ant colony algorithm

Stochastic time-dependent vehicle routing problem: Mathematical models and ant colony algorithm

Urban Freight Management with Stochastic Time-Dependent Travel Times and Application to Large-Scale Transportation Networks

An adaptive parallel route construction heuristic for the vehicle routing problem with time windows constraints

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