An efficient two-phase exact algorithm for the automated truck freight transportation problem
Introduction
Efficient shipments of cargos has attracted much attention and considerable freight transportation planning problems have been investigated extensively over the past decades (Goksal et al., 2013, Prins, 2004, Shaabani and Kamalabadi, 2016). However, increasing travel demand results in increasingly severe congestion, which causes many problems in transportation, such as low efficiency, unpredictable transport time, traffic accidents, and fuel waste. These problems increasingly prevent the freight transportation from being operated in an efficient, reliable and safe fashion (Fang, Chu, Mammar, & Che, 2013). Introducing automated driving for trucks would be a promising solution to cope with such challenge, as automated trucks could provide remarkable advantages such as high safety and efficiency, and lower fuel consumption.
Unlike manually driven trucks, automated ones must have the ability of detecting possible dangers and responding to them correctly and promptly. Dedicated truck lanes would be ideal in this sense. Since constructing new network dedicated to automated trucks may be infeasible due to the high costs and limited geographic space, converting existing general-purpose (GP) lanes in the existing network to dedicated ones is an effective alternative. But due to the exclusive use of reserved lanes by automated trucks, the available lanes in the network for GP vehicles are reduced, and negative impact, such as the increase in travel time of GP vehicles, will be generated on the adjacent lanes. It is necessary to well decide appropriate lanes to be reserved to achieve the safe and time-guaranteed automated truck transportation, while minimizing the negative traffic impact. Such an optimization problem is called the automated truck transportation problem with lane reservation (ATP) (Fang et al., 2013). We note that there have also been studies investigating lane reservation for other applications, such as large sport events, hazardous material transportation, bus transit (Che et al., 2015, Fang et al., 2014, Fang et al., 2015, Fang et al., 2012, Wu et al., 2013, Wu et al., 2016, Wu et al., 2015, Wu et al., 2009, Zhou et al., 2013).
Fang et al. (2013) have formulated an integer linear program (ILP) and developed an exact cut-and-solve algorithm for the ATP. However, due to the NP-hardness of the ATP, their proposed methods become difficult to solve large-size problems within acceptable computational time. In this paper, we first provide an improved ILP by adding valid inequalities. Then, we identify that several special cases of the ATP are classical combinatorial optimization problems. Based on the analyzed properties, a new efficient two-phase exact algorithm is developed. Computational results on 120 benchmark and 210 new larger-size instances with up to 700 nodes and 55 tasks confirm the effectiveness of the proposed algorithm.
The remainder of the paper is organized as follows. Section 2, recalls the problem description and provides the improved ILP. In Section 3, we derive several optimal properties of the ATP. Based on them, a new efficient exact algorithm is presented in Section 4. Section 5 reports the computational results. Section 6 concludes this study.
Section snippets
Problem description and formulation
The ATP considered in this study has been addressed by Fang et al. (2013). For the sake of self-consistency, the problem description is first recalled as follows.
The ATP can be defined on a transportation network that can be represented by a directed graph with a node set N and an arc set A. A node (resp. an arc) represents a road intersection (resp. a road segment). Given a set of automated truck transportation tasks to be accomplished and their corresponding origin-destination (OD)
Property analysis for the ATP
In this section, we first investigate several special cases for the ATP. Note that these special cases correspond to classical combinatorial optimization problems and can be tackled using existing techniques. The potential benefits are that if an instance is recognized as one special case of them, then it can be efficiently solved accordingly. Then, the ATP in the general case is analyzed.
Two-phase exact algorithm for the ATP
For an ATP in general case, Fang et al. (2013) proposed a cut-and-solve algorithm, which can solve problem instances with up to 150 nodes in the network and 30 tasks within 18,000 CPU seconds. In this paper, a new efficient two-phase exact algorithm is developed to efficiently solve the larger-size ATP. The algorithm is composed of two major phases. In the first phase, all feasible paths respecting the travel deadline constraint are enumerated for each task . An optimal lane reservation
Computational experiments
In this section, we conduct numerical computational experiments to show the performance of the proposed algorithm. Our algorithm is coded in C++ language and combined with Yen’s -shortest loopless path algorithm (Yen, 1971) and CPLEX (12.6) IP solver with default settings. All the experiments are done on a PC with 2.5 GHz and 2.95 GB RAM with windows 7 system.
The performance of the proposed model and algorithm is evaluated on 74 groups of instances with five instances each group, including 160
Conclusion
In this paper, we have revisited the automated truck transportation problem with lane reservation proposed by Fang et al. (2013). For the problem, we first propose valid inequalities for the integer linear program proposed by Fang et al. (2013). Computational comparison results indicate that these valid inequalities are effective in saving computational time. Furthermore, we have investigated several special cases of the considered problem, which can be identified to be classical combinatorial
Acknowledgements
This work was supported in part by the National Natural Science Foundation of China under Grants 71571061 and 71471145, in part by the Natural Science Foundation of Fujian Province, China under Grant 2015J05137 and by the Scientific Research Foundation of Fuzhou University under Grants GXRC201709, 14SKQ05.
References (20)
- et al.
An optimal algorithm for automated truck freight transportation via lane reservation strategy
Transportation Research Part C: Emerging Technologies
(2013) - et al.
A new cut-and-solve and cutting plane combined approach for the capacitated lane reservation problem
Computers & Industrial Engineering
(2015) - et al.
A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery
Computers and Industrial Engineering
(2013) - et al.
Impact of a dedicated lane on the capacity and the level of service of an urban motorway
Procedia - Social and Behavioral Sciences
(2011) A simple and effective evolutionary algorithm for the vehicle routing problem
Computers & Operations Research
(2004)- et al.
An efficient population-based simulated annealing algorithm for the multi-product multi-retailer perishable inventory routing problem
Computers & Industrial Engineering
(2016) Path routing in mesh optical networks
(2007)- et al.
Improved quantum-inspired evolutionary algorithm for large-size lane reservation
IEEE Transactions on Systems, Man, and Cybernetics: Systems
(2015) A note on two problems in connexion with graphs
Numerische mathematik
(1959)- et al.
A cut-and-solve-based algorithm for optimal lane reservation with dynamic link travel times
International Journal of Production Research
(2014)
Cited by (29)
A review of unmanned vehicle distribution optimization models and algorithms
2023, Journal of Traffic and Transportation Engineering (English Edition)Daily load planning under different autonomous truck deployment scenarios
2022, Transportation Research Part E: Logistics and Transportation ReviewAutonomous robot-driven deliveries: A review of recent developments and future directions
2022, Transportation Research Part E: Logistics and Transportation ReviewCitation Excerpt :The problem is modeled, with Integer Linear Program (ILP) formulations with cut and solve algorithms, to minimize the total adverse effects of lane reservations like less road capacity for general vehicles and traffic congestion in parallel lanes. In a consequent study by Wu et al. (2017), ATP-LR is addressed by a two-phase exact algorithm. Here, first, all the feasible routes are identified, then an optimal lane reservation scheme and delivery task path are determined.
A bi-level programming model for the optimal lane reservation problem
2022, Expert Systems with ApplicationsService-oriented distributionally robust lane reservation
2022, Journal of Industrial Information IntegrationA new exact algorithm for the shortest path problem: An optimized shortest distance matrix
2021, Computers and Industrial EngineeringCitation Excerpt :Sedeño-noda and Colebrook (2019) used Dijkstra's algorithm to find all non-dominated points in the solution to the bi-objective shortest path problem, which generalized the Dijkstra algorithm for bi-objective cases. Wu, Chu, Che, and Fang (2017) developed a new efficient two-phase exact algorithm for the automated truck transportation freight problem with lane reservation. Chen, Shen, Chen, and Yang (2014) built a dynamic road network model for vehicle evacuation based on Dijkstra's algorithm.