Traffic Aware Many-Objective Dynamic Route Planning

Liu, Yijie; Enayatollahi, Fatemeh; Thulasiraman, Parimala

doi:10.1109/ssci44817.2019.9002725

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…The other problems such as pollution routing problem [111], [112], ship weather routing problem [113], urban freight transportation planning problem [114], many-objective dynamic route planning [115], VRP with demand responsive transport [116], [117], VRP with time windows [118], and other routing problems [119], [120], [121], [122], [123], [124] are considered under the category of VRPs.…”

Section: A Nsga-ii For Mocopsmentioning

confidence: 99%

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A Comprehensive Review on NSGA-II for Multi-Objective Combinatorial Optimization Problems

2021

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This paper provides an extensive review of the popular multi-objective optimization algorithm NSGA-II for selected combinatorial optimization problems viz. assignment problem, allocation problem, travelling salesman problem, vehicle routing problem, scheduling problem, and knapsack problem. It is identified that based on the manner in which NSGA-II has been implemented for solving the aforementioned group of problems, there can be three categories: Conventional NSGA-II, where the authors have implemented the basic version of NSGA-II, without making any changes in the operators; the second one is Modified NSGA-II, where the researchers have implemented NSGA-II after making some changes into it and finally, Hybrid NSGA-II variants, where the researchers have hybridized the conventional and modified NSGA-II with some other technique. The article analyses the modifications in NSGA-II and also discusses the various performance assessment techniques used by the researchers, i.e., test instances, performance metrics, statistical tests, case studies, benchmarking with other state-of-the-art algorithms. Additionally, the paper also provides a brief bibliometric analysis based on the work done in this study.

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Section: A Nsga-ii For Mocopsmentioning

confidence: 99%

“…Liu et al [115] proposed a four-objective dynamic routing planning problem in which a novel objective was considered for simpler routing and better user experience. NSGA-II was designed and used a node-based crossover operator to solve the proposed model to obtain a trade-off among the four objectives.…”

Section: C) Vehicle Routing Problemmentioning

confidence: 99%

A Comprehensive Review on NSGA-II for Multi-Objective Combinatorial Optimization Problems

2021

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Cooperative, collaborative, coevolutionary multi-objective optimization on CPU-GPU multi-core

Sun,

Liu,

Thulasiraman

2024

J Supercomput

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Based on Improved NSGA-II Algorithm for Solving Time-Dependent Green Vehicle Routing Problem of Urban Waste Removal with the Consideration of Traffic Congestion: A Case Study in China

Gao

et al. 2023

Systems

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The dense population and the large amount of domestic waste generated make it difficult to determine the best route and departure time for waste removal trucks in a city. Aiming at the problems of municipal solid waste (MSW) removal and transportation not in time, high collection and transportation costs and high carbon emissions, this paper studies the vehicle routing problem of municipal solid waste removal under the influence of time-dependent travel time, traffic congestion and carbon emissions. In this paper, a dual objective model with the lowest total economic cost and the highest garbage removal efficiency is established, and a DCD-DE-NSGAII algorithm based on Dynamic Crowding Distance and Differential Evolution is designed to improve the search ability, improve the convergence speed and increase the diversity of the optimal solution set. The results show that: according to the actual situation of garbage collection and transportation, the method can scientifically plan the garbage collection and transportation route, give a reasonable garbage collection scheme and departure time, and effectively avoid traffic congestion time; Through algorithm comparison, the algorithm and model proposed in this paper can reduce collection and transportation costs, improve transportation efficiency and reduce environmental pollution.

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Traffic Aware Many-Objective Dynamic Route Planning

Cited by 3 publications

References 11 publications

A Comprehensive Review on NSGA-II for Multi-Objective Combinatorial Optimization Problems

A Comprehensive Review on NSGA-II for Multi-Objective Combinatorial Optimization Problems

Cooperative, collaborative, coevolutionary multi-objective optimization on CPU-GPU multi-core

Based on Improved NSGA-II Algorithm for Solving Time-Dependent Green Vehicle Routing Problem of Urban Waste Removal with the Consideration of Traffic Congestion: A Case Study in China

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