An Effective Local Search Algorithm for the Multidepot Cumulative Capacitated Vehicle Routing Problem

Wang, Xinyu; Choi, Tsan‐Ming; Li, Zhiying; Shao, Shuai

doi:10.1109/tsmc.2019.2938298

Cited by 37 publications

(12 citation statements)

References 38 publications

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“…Research on drone delivery originally derived from investigations into vehicle routing problems (VRPs). In urban logistics, especially in the last-mile delivery field, the key objective of VRP and its variants is determining a set of optimal routes performed by vehicles with limited capacity and operational constraints to serve a certain group of customers (e.g., Lahyani et al, 2015;Laporte, 2009;Villegas et al, 2013;Wang & Sheu, 2019;Wang, Choi, et al, 2020;Wang, Poikonen, et al, 2017). By incorporating drone delivery to replace or assist the traditional truck-based transport mode, new challenges are arising.…”

Section: Drone Routing and Operation Optimisationmentioning

confidence: 99%

Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

et al. 2021

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Alongside the rise of ‘last-mile’ delivery in contemporary urban logistics, drones have demonstrate commercial potential, given their outstanding triple-bottom-line performance. However, as a lithium-ion battery-powered device, drones’ social and environmental merits can be overturned by battery recycling and disposal. To maintain economic performance, yet minimise environmental negatives, fleet sharing is widely applied in the transportation field, with the aim of creating synergies within industry and increasing overall fleet use. However, if a sharing platform’s transparency is doubted, the sharing ability of the platform will be discounted. Known for its transparent and secure merits, blockchain technology provides new opportunities to improve existing sharing solutions. In particular, the decentralised structure and data encryption algorithm offered by blockchain allow every participant equal access to shared resources without undermining security issues. Therefore, this study explores the implementation of a blockchain-enabled fleet sharing solution to optimise drone operations, with consideration of battery wear and disposal effects. Unlike classical vehicle routing with fleet sharing problems, this research is more challenging, with multiple objectives (i.e., shortest path and fewest charging times), and considers different levels of sharing abilities. In this study, we propose a mixed-integer programming model to formulate the intended problem and solve the problem with a tailored branch-and-price algorithm. Through extensive experiments, the computational performance of our proposed solution is first articulated, and then the effectiveness of using blockchain to improve overall optimisation is reflected, and a series of critical influential factors with managerial significance are demonstrated.

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Section: Drone Routing and Operation Optimisationmentioning

confidence: 99%

Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

et al. 2021

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“…From the results in Table 1, we can observe that F1 and F2 found the optimal solutions for all the instances. The models adapted from [19] and [44] were able to find the optimal solution for the smallest instances with 10 customers. For the instances with 25 customers, after two hours, we observed considerably optimality gaps of at least 29% (Lalla's model) and 38% ( Wang's model).…”

Section: Results Obtained Considering Benchmark Instancesmentioning

confidence: 99%

“…In this section, we report on the computational experiments carried out with the aim of testing the proposed models as well as the solution approach. We first assessed the efficiency of the two mathematical formulations, implemented using the AMPL optimization language [10] and solved by Gurobi 8.1.0 [14] within a time limit of 7200 s. To have a comparison, we also re-implemented (excluding the constraints on the capacity of vehicles) the models proposed for the multi-depot CCVRP, namely the one proposed in [19] and [44]. We refer to these models by the authors' names and denote our first and second mathematical formulations in Sect.…”

Section: Computational Experimentsmentioning

confidence: 99%

“…The authors also proposed a partial optimization metaheuristic that decomposes the problem into sub-problems, later solved using either an approximate or an exact approach. To overcome the computational challenge posed by large-scale multi-depot CCVRP instances, a simple and efficient heuristic was proposed in [44] able to outperform the heuristic presented in [19] in terms of solution quality, computational time, as well as stability.…”

Section: Introductionmentioning

confidence: 99%

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The multi-depot k-traveling repairman problem

et al. 2022

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In this paper, we study the multi-depot k-traveling repairman problem. This problem extends the traditional traveling repairman problem to the multi-depot case. Its objective, similar to the single depot variant, is the minimization of the sum of the arrival times to customers. We propose two distinct formulations to model the problem, obtained on layered graphs. In order to find feasible solutions for the largest instances, we propose a hybrid genetic algorithm where initial solutions are built using a splitting heuristic and a local search is embedded into the genetic algorithm. The efficiency of the mathematical formulations and of the solution approach are investigated through computational experiments. The proposed models are scalable enough to solve instances up to 240 customers.

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“…In [54], the authors proposed a hybrid ant colony algorithm to solve a multi-depot cumulative VRP (MDCCVRP) as applied to postdisaster route planning. More recently, an LS-based algorithm was presented in [55] to solve the same theoretical problem, which was also studied in [24], in which the authors proposed a matheuristic that decomposed the problem into subproblems that could be easily solved to optimality. Their approach was called partial optimization metaheuristic under special intensification conditions.…”

Section: ) Cumulative Vehicle Routing Problemsmentioning

confidence: 99%

The Multi-Depot Cumulative Vehicle Routing Problem With Mandatory Visit Times and Minimum Delayed Latency

et al. 2021

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This paper introduces a novel variant of the cumulative vehicle routing problem (CCVRP) that deals with home health care (HHC) logistics. It includes multiple nonfixed depots and emergency trips from patients to the closest depot. The aim is to minimize the system's delayed latency by satisfying mandatory visit times. Delayed latency corresponds to caregivers' total overtime hours worked while visiting patients. A new mixed-integer linear programming model is proposed to address this problem. Computational experiments, with more than 165 new benchmark instances, are carried out using the CPLEX and Gurobi MIP solvers. The results indicate that patients' geographical distribution directly impacts the complexity of the problem. An analysis of the model parameters proves that instances with more depots/vehicles or longer workdays are significantly easier to solve than are original cases. The results show that Gurobi outperforms CPLEX in 55% of the instances analyzed, while CPLEX performs better in only 16% of them. To the best of our knowledge, this is the first VRP that minimizes delayed latency and the first HHC routing study to use a cumulative objective function.

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An Effective Local Search Algorithm for the Multidepot Cumulative Capacitated Vehicle Routing Problem

Cited by 37 publications

References 38 publications

Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

The multi-depot k-traveling repairman problem

The Multi-Depot Cumulative Vehicle Routing Problem With Mandatory Visit Times and Minimum Delayed Latency

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