Divide-and-conquer large scale capacitated arc routing problems with route cutting off decomposition

Zhang, Yuzhou; Mei, Yi; Zhang, Buzhong; Jiang, Keqin

doi:10.1016/j.ins.2020.11.011

Cited by 16 publications

(3 citation statements)

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“…e capacitated arc routing problem is aimed to determine an optimal traversal of an arc subset of a graph by some capacitated vehicles [1] and has been widely studied in the past years, such as by converting to the capacitated vehicle routing problem [30,31], or directly by exact optimization methods [32,33], or by some lower bounding procedures [34][35][36][37] and heuristic methods [13,[38][39][40][41]. Among them, the "Partition-First, Route-Second" heuristic has been widely used in CARP and its variants and has been proved to be effective [13][14][15][16][17]. is paper adopts this heuristic idea to decompose the original problem into some smaller subproblems by partitioning the arcs into some subzones.…”

Section: Literature Reviewmentioning

confidence: 99%

“…On the upper level, the road network is partitioned into subzones to decompose the problem into multiple smaller subproblems. is idea of partitioning streets into clusters has been widely used in the classical CARP and its variants [13][14][15][16][17]. In the setting of our problem, the road network partition provides constraints of feasible operation area and reward to each worker, preventing the potential conflict of workers' operations.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Capacitated Arc Routing Problem in E-Bike Sharing System: A Monte Carlo Tree Search Approach

Tan

Xie

2021

Journal of Advanced Transportation

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This paper studies a dynamic capacitated arc routing problem for battery replacement in an e-bike sharing system, where workers replace batteries for underpowered e-bikes along street segments dynamically. The objective is to replace as many batteries as possible and minimize pickup failures. The temporal dependency of the routing decisions, the conflict of the workers’ operations, and the stochastic and dynamic nature of user demands all make this a difficult problem. To cope with these difficulties, a “Partition-First, Route-Second” bi-level solution framework is adopted to describe the problem in two different time scales. On the large time scale, a spatiotemporal partitioning method, which divides the road network into nonoverlapping subzones, is proposed to decompose the problem. On the small time scale, this paper models the routing decision process of individual worker as a Markov Decision Process. We adopt a lookahead policy that simulates future information and decisions over some horizons to evaluate the long-term influence of current feasible decisions. A Monte Carlo Tree Search algorithm is also used to improve the simulation efficiency. By performing numerical computation experiments on a test case study and comparing with some benchmarking policies, we demonstrate the effectiveness and efficiency of the suggested method.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Capacitated Arc Routing Problem in E-Bike Sharing System: A Monte Carlo Tree Search Approach

Tan

Xie

2021

Journal of Advanced Transportation

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“…Traditionally, CARP focuses on static environments, where all the details of the problems, such as the demands of tasks and the traversal costs of streets, can be precisely known beforehand (MacLachlan and Mei, 2021;Zhang et al, 2021). However, reallife often contradicts this assumption (Mei and Zhang, 2018;Zhu et al, 2018;Liu et al, 2020).…”

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confidence: 99%

Route Stability in the Uncertain Capacitated Arc Routing Problem

et al. 2022

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Power line inspections in a microgrid can be modeled as the uncertain capacitated arc routing problem, which is a classic combinatorial optimization problem. As an evolutionary computation method, genetic programming is used as a hyper-heuristic method to automatically evolve routing policies that can make real-time decisions in an uncertain environment. Most existing research on genetic programming hyper-heuristic for the uncertain capacitated arc routing problem only focuses on optimizing the total cost of solutions. As a result, the actual routes directed by the routing policies evolved by genetic programming hyper-heuristic are usually not stable, i.e., the routes have large fluctuations in different uncertain environments. However, for marketing or considering the drivers’ and customers’ perspectives, the routes should not be changed too often or too much. Addressing this problem, this study first proposes a method to estimate the similarity between two routes and then extends it for evaluating the stability of the routes in uncertain environments. A novel genetic programming hyper-heuristic, which considers two objectives, i.e., the solution quality (total cost) and the stability of routes, was designed. Experimental studies demonstrate that the proposed genetic programming is hyper-heuristic with stability in consideration and can obtain more stable solutions than the traditional algorithm, without deteriorating the total cost. The approach provided in this study can be easily extended to solving other combinatorial optimization problems in the microgrid.

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Dynamic matrix-based evolutionary algorithm for large-scale sparse multiobjective optimization problems

Qiu,

Hu,

Ren

et al. 2023

Memetic Comp.

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Divide-and-conquer large scale capacitated arc routing problems with route cutting off decomposition

Cited by 16 publications

References 58 publications

Dynamic Capacitated Arc Routing Problem in E-Bike Sharing System: A Monte Carlo Tree Search Approach

Dynamic Capacitated Arc Routing Problem in E-Bike Sharing System: A Monte Carlo Tree Search Approach

Route Stability in the Uncertain Capacitated Arc Routing Problem

Dynamic matrix-based evolutionary algorithm for large-scale sparse multiobjective optimization problems

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