The Split Delivery Vehicle Routing Problem with three-dimensional loading constraints

Bortfeldt, Andreas; Yi, Junmin

doi:10.1016/j.ejor.2019.09.024

Cited by 76 publications

(24 citation statements)

References 51 publications

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“…Results for Class 1 instances 514TableA1shows the results for the Class 1 instances, where the best costs are compared 515 with the other four previous frameworks. The CGA-TS-LNS found better and higher 516 quality solutions for the 6 most complex instances(30)(31)(32)(33)(34)(35)(36) and matched the BKS for 28 517 instances. In addition, Figure12shows the average cost of the solutions found by the 518 CGA-TS-LNS for the 36 instances of Class 1 is lower than all previous approaches, and 519 lower than the average cost of all the BKS.…”

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confidence: 87%

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A Multi-Start Algorithm for Solving the Capacitated Vehicle Routing Problem with Two-Dimensional Loading Constraints

Fava¹,

Furtado²,

Helfer³

et al. 2021

Preprint

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This work presents a multi-start algorithm for solving the capacitated vehicle routing problem with two-dimensional loading constraints (2L-CVRP) allowing for the rotation of goods. Researches dedicated to graph theory and symmetry considered the vehicle routing problem as a classical application. This problem has complex aspects that stimulate the use of advanced algorithms and symmetry in graphs. The use of graph modeling of the 2L-CVRP problem by undirected graph allowed the high performance of the algorithm. The developed algorithm is based on metaheuristics such as the Constructive Genetic Algorithm (CGA), to construct promising initial solutions; a Tabu Search (TS), to improve the initial solutions on the routing problem; and a Large Neighborhood Search (LNS), for the loading subproblem. Although each one of these algorithms allowed to solve parts of the 2L-CVRP, the combination of these three algorithms to solve this problem was unprecedented in the scientific literature. In our approach, a parallel mechanism for checking the loading feasibility of routes was implemented using multi-threading programming to improve the performance. Additionally, memory structures, like hash-tables, were implemented to save time by storing and querying previously evaluated results for the loading feasibility of routes. For benchmarks, tests were done on well-known instances available in the literature. The results proved that the framework matched or outperformed most of the previous approaches. As the main contribution, this work brings higher quality solutions for large-size instances of the pure CVRP. This paper involves themes related to the symmetry journal, mainly complex algorithms, graphs, search strategies, complexity, graph modeling, and genetic algorithms. In addition, the paper especially focuses on topic-related aspects of special interest of the community involved in symmetry studies, such as, graph algorithms and graph theory.

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confidence: 87%

“…The VRP is addressed in studies dedicated to graph theory and algorithms [5] to solve the 3L-CVRP with backhauls and time windows. Recently, Bortfeldt and Yi [35] 119 proposed a hybrid algorithm to solve the split delivery VRP (SDVRP) with the 3L-CVRP.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Start Algorithm for Solving the Capacitated Vehicle Routing Problem with Two-Dimensional Loading Constraints

Fava¹,

Furtado²,

Helfer³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Reference [35] focused on the split delivery vehicle routing problem with three-dimensional loading constraints combining vehicle routing (3L-SDVRP) with a proposed hybrid algorithm consisting of a local search algorithm for routing and a genetic algorithm and several construction heuristics for packing. Reference [36] investigated a vehicle routing problem with three-dimensional loading constraints and mixed backhauls (3L-VRPMB) and proposed a hybrid metaheuristic consisting of a reactive tabu search for the routing problem and different packing heuristics for the loading problem.…”

Section: Related Workmentioning

confidence: 99%

A Double Traveling Salesman Problem With Three-Dimensional Loading Constraints for Bulky Item Delivery

et al. 2021

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This article considers bulky item delivery problems in which multiple items are retrieved and loaded onto a vehicle from different warehouses and then delivered. This problem is described as a double traveling salesman problem with three-dimensional container loading constraints with multiple stacks. The double TSP with multiple stacks is used to determining the shortest route performing pickups and deliveries in two separated networks (one for pickups and one for deliveries) using only one container. Repacking is not allowed after loading the items into the container. An integer linear programming model is proposed to solve this problem, a standard genetic algorithm and an improved genetic algorithm is designed. In the improved genetic algorithm, a Lin-Kernighan algorithm is used to improve the delivery route, a k-means clustering algorithm, and a heuristic packing scheme improvement rules work together to improve the loading route. The results show that the improved genetic algorithm is superior to the standard genetic algorithm in large scale problems.INDEX TERMS Double traveling salesman problem, three-dimensional container loading, bulky item delivery, genetic algorithm.

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“…GA does not require to calculate the derivatives of the objective function, and its performance in optimizing complex mathematical models (e.g. vehicle routing problems [36][37][38][39]) is promising [8].…”

Section: Solution Algorithmmentioning

confidence: 99%

Optimizing Multi-Terminal Customized Bus Service With Mixed Fleet

Sun

Chien

et al. 2020

IEEE Access

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The customized bus (CB) transit is recognized as an effective transportation mode offering more flexible and demand-responsive service than traditional bus transit with fixed route and schedule, especially during the peak hours. The novelty of this study is the development of a mixed integer non-linear model for optimizing multi-terminal CB service in an urban setting. According to the estimated spatiotemporal passenger demand, the objective total cost, consisting of supplier's and users' costs, is minimized subject to capacity and time window constraints. A mixed bus fleet with various bus sizes is employed to accommodate passenger demand, which increases vehicle utilization and reduces supplier's cost. The inconvenience of passengers caused by early arrival at the destination is treated as penalty and considered in users' cost. The study optimization problem is combinatorial with many decision variables including trip assignment, bus routing and associated timetables, and fleet size. A hybrid genetic algorithm (HGA) which integrates the features of genetic algorithm (GA) and simulated annealing (SA) is developed to effectively search for the optimal solution. A real-world CB network is employed to demonstrate the applicability of the developed model and explore the relation between the model parameters and optimized results. It was found that the total cost can be reduced by 16.5% after employing multiple terminals and a mixed bus fleet.

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The Split Delivery Vehicle Routing Problem with three-dimensional loading constraints

Cited by 76 publications

References 51 publications

A Multi-Start Algorithm for Solving the Capacitated Vehicle Routing Problem with Two-Dimensional Loading Constraints

A Multi-Start Algorithm for Solving the Capacitated Vehicle Routing Problem with Two-Dimensional Loading Constraints

A Double Traveling Salesman Problem With Three-Dimensional Loading Constraints for Bulky Item Delivery

Optimizing Multi-Terminal Customized Bus Service With Mixed Fleet

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