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Proceedings ArticleDOI

Vehicle Navigation Protocol in Real-Time Fleet Management

12 Mar 2020-pp 248-251

TL;DR: The use of parallel computing strategies for solving real-time vehicle routing problems is highlighted, related to linear optimisation and falls under the domain of logistics and transport.

AbstractIn Real-Time Fleet Management, vehicle routes are built dynamically according to travel durations, location of the vehicles and also customer requests which are revealed gradually To account for such situations, algorithms which are fast and can accommodate the uncertainty are needed We here highlights the use of parallel computing strategies for solving real-time vehicle routing problems The vehicle routing problem is related to linear optimisation and falls under the domain of logistics and transport Vehicle routing problems comprise of determining optimal vehicle routes according to various constraints such as the total demand should not exceed the total capacity, service durations are met The objectives of solving the Vehicle Routing Protocol varies depending upon the dynamically of the system In general, systems, which are weakly dynamic, focus on optimising or minimising the routing costs The systems, which are strongly dynamic, focus more on minimising the expected response time

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References
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Journal ArticleDOI
TL;DR: An iterative procedure is developed that enables the rapid selection of an optimum or near-optimum route and has been programmed for a digital computer but is also suitable for hand computation.
Abstract: The optimum routing of a fleet of trucks of varying capacities from a central depot to a number of delivery points may require a selection from a very large number of possible routes, if the number of delivery points is also large. This paper, after considering certain theoretical aspects of the problem, develops an iterative procedure that enables the rapid selection of an optimum or near-optimum route. It has been programmed for a digital computer but is also suitable for hand computation.

3,454 citations

Journal ArticleDOI
TL;DR: A GA without trip delimiters, hybridized with a local search procedure is proposed, which outperforms most published TS heuristics on the 14 classical Christofides instances and becomes the best solution method for the 20 large-scale instances generated by Golden et al.
Abstract: The vehicle routing problem (VRP) plays a central role in the optimization of distribution networks. Since some classical instances with 75 nodes resist the best exact solution methods, most researchers concentrate on metaheuristics for solving real-life problems. Contrary to the VRP with time windows, no genetic algorithm (GA) can compete with the powerful tabu search (TS) methods designed for the VRP. This paper bridges the gap by presenting a relatively simple but effective hybrid GA. In terms of average solution cost, this algorithm outperforms most published TS heuristics on the 14 classical Christofides instances and becomes the best solution method for the 20 large-scale instances generated by Golden et al. Scope and purpose The framework of this research is the development of effective metaheuristics for hard combinatorial optimization problems met in vehicle routing. It is surprising to notice in the literature the absence of effective genetic algorithms (GA) for the vehicle routing problem (VRP, the main capacitated node routing problem), contrary to node routing problems with time windows or arc routing problems. Earlier attempts were based on chromosomes with trip delimiters and needed a repair procedure to get feasible children after each crossover. Such procedures are known to weaken the genetic transmission of information from parents to children. This paper proposes a GA without trip delimiters, hybridized with a local search procedure. At any time, a chromosome can be converted into an optimal VRP solution (subject to chromosome sequence), thanks to a special splitting procedure. This design choice avoids repair procedures and enables the use of classical crossovers like OX. The resulting algorithm is flexible, relatively simple, and very effective when applied to two sets of standard benchmark instances ranging from 50 to 483 customers.

896 citations

Journal ArticleDOI
Abstract: A Green Vehicle Routing Problem (G-VRP) is formulated and solution techniques are developed to aid organizations with alternative fuel-powered vehicle fleets in overcoming difficulties that exist as a result of limited vehicle driving range in conjunction with limited refueling infrastructure The G-VRP is formulated as a mixed integer linear program Two construction heuristics, the Modified Clarke and Wright Savings heuristic and the Density-Based Clustering Algorithm, and a customized improvement technique, are developed Results of numerical experiments show that the heuristics perform well Moreover, problem feasibility depends on customer and station location configurations Implications of technology adoption on operations are discussed

595 citations

Journal ArticleDOI
TL;DR: This paper proposes a tabu search approach characterized by a holding list and a mechanism to force dense packing within a route that allows time windows to be relaxed by introducing the notion of penalty for lateness.
Abstract: This paper introduces a variant of the vehicle routing problem with time windows where a limited number of vehicles is given (m-VRPTW). Under this scenario, a feasible solution is one that may contain either unserved customers and/or relaxed time windows. We provide a computable upper bound to the problem. To solve the problem, we propose a tabu search approach characterized by a holding list and a mechanism to force dense packing within a route. We also allow time windows to be relaxed by introducing the notion of penalty for lateness. In our approach, customer jobs are inserted based on a hierarchical objective function that captures multiple objectives. Computational results on benchmark problems show that our approach yields solutions that are competitive to best-published results on VRPTW. On m-VRPTW instances, experiments show that our approach produces solutions that are very close to computed upper bounds. Moreover, as the number of vehicles decreases, the routes become more densely packed monotically. This shows that our approach is good from both the optimality as well as stability point of view.

239 citations


"Vehicle Navigation Protocol in Real..." refers background in this paper

  • ...This minimum cost route that is drawn by this module is sent to it by the Solution module[8]....

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  • ...Sun Zhongyue [8] has proposed a new solution to bypass the disadvantages of exact and heuristic algorithms with multiple constraints....

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  • ...[9] Sun Zhongyue and Guan Zhongliang, "Vehicle routing problem based on object-oriented discrete event simulation," 2010 2nd International Conference on Advanced Computer Control, Shenyang, IEEE, 2010, pp. 638-643. doi: 10.1109/ICACC.2010.5486792....

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Journal ArticleDOI
TL;DR: The state of the art of City VRP is identified, the core challenging issues are highlighted, and some potential research area in this field that have remained underexplored are suggested.
Abstract: Lately, the Vehicle Routing Problem (VRP) in the city, known as City VRP, has gained popularity with its importance in city logistics. Similar to city logistics, City VRP mainly differs from conventional VRP in terms of the stakeholders involved, namely the shipper, carrier, resident, and administrator. Accordingly, this paper surveys the City VRP literature categorized by stakeholders and summarizes the constraints, models, and solution methods for VRP in urban cities. City VRPs are also analyzed based on the problem of interest considered by the stakeholders and the corresponding models that have been proposed in response. Through this review, we identify the state of the art of City VRP, highlight the core challenging issues, and suggest some potential research area in this field that have remained underexplored.

94 citations


"Vehicle Navigation Protocol in Real..." refers background in this paper

  • ...The Vehicle module and the Solution module work in synchrony on order to develop various partial routes and combined routes on various different costs and finally arrive at the one with the minimum cost[7]....

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  • ...In Hoong Chuin Lau [7] a variant of VRP has been discussed which is constrained with time windows and a limited number of vehicles....

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