A Decision Support Tool for Urban Freight Transport Planning Based on a Multi-Objective Evolutionary Algorithm

Miguel, Fábio; Frutos, Mariano; Tohmé, Fernando; Méndez, Máximo

doi:10.1109/access.2019.2949948

Cited by 14 publications

(12 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…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%

See 1 more Smart Citation

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

2021

View full text Add to dashboard Cite

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.

show abstract

Section: A Nsga-ii For Mocopsmentioning

confidence: 99%

“…Miguel et al [114] addressed a multi-depot time-dependent capacitated VRP with time windows problem in urban freight transport planning. A hybrid variant of NSGA-II was developed that incorporated the knowledge information of the problem in the chromosomes and used a newly designed ERX-MD recombination operator.…”

Section: C) Vehicle Routing Problemmentioning

confidence: 99%

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

2021

View full text Add to dashboard Cite

show abstract

“…Neural systems as e.g. [33], [35], can also be used. Amongst them, the neuroevolution approach introduced in [36]- [38], and successfully used in real-world application such as [6], appear to be the most promising choice, as shown in each case study of Section IV, since capable of optimising the structure of neural networks to best perform on the available data set.…”

Section: Local Decision-making (Ldm)mentioning

confidence: 99%

A Robust Decision-Making Framework Based on Collaborative Agents

et al. 2020

View full text Add to dashboard Cite

Making decisions under uncertainty is very challenging but necessary as most real-world scenarios are plagued by disturbances that can be generated internally, by the hardware itself, or externally, by the environment. Hence, we propose a general decision-making framework which can be adapted to optimally address the most heterogeneous real-world domains without being significantly affected by undesired disturbances. Our paper presents a multi-agent based structure in which agents are capable of individual decision-making but also interact to perform subsequent, and more robust, collaborative decisionmaking processes. The complexity of each software agent can be kept quite low without a deterioration of the performance since an intelligent and robust-to-uncertainty decision-making behaviour arises when their locally produced measure of support are shared and exploited collaboratively. We show that by equipping agents with classic computational intelligence techniques, to extract features and generate measure of supports, complex hybrid multi-agent software structures capable of handling uncertainty can be easily designed. The resulting multi-agent systems generated with this approach are based on a two-phases decision-making methodology which first runs parallel local decision making processes to then aggregate the corresponding outputs to improve upon the accuracy of the system. To highlight the potential of this approach, we provided multiple implementations of the general framework and compared them over four different application scenarios. Results are promising and show that having a second collaborative decisionmaking process is always beneficial.

show abstract

“…Evolutionary game analysis on the implementation of subsidy policy for sustain able transportation development is studied [16]. As for the spatial scale of the problem being solved in the field of trans port, the gametheoretical approach is widely used at the re gional level [4, 17,18] and at the macroscale level of the trans port market as a whole [7,19].…”

mentioning

confidence: 99%

“…A hybrid genetic al gorithm is also developed by the authors of the paper [12] for the purposes of designing the collaborative transport network for deliveries of the oil and gas drilling equipment. The evolu tionary multiobjective algorithm was applied as well in the paper [17]: the authors propose to use it as the main tool in order to solve the planning problems of a merchandise distri bution firm that dispatches small volume fractional loads of fresh foods in a city.…”

mentioning

confidence: 99%

Choosing a servicing company’s strategy while interacting with freight owners at the road transport market

Nugymanova¹,

Nurgaliyeva²,

Zhanbirov³

et al. 2021

Nauk. visn. nat. hirn. univ.

View full text Add to dashboard Cite

Purpose. To develop the methodology for choosing the strategies of freight forwarding companies in the situation of interaction with freight owners as customers of forwarding services. Methodology. The game-theoretical approach is used to formalize the conflict situation between a freight forwarding company and a cargo owner. A set of services proposed by forwarders is used as the base in order to represent possible strategies of a forwarder as the vector of probabilities that the respective services are provided for a client. The strategies of the cargo owner are represented as a binary variable that shows whether the client uses the provided services or not. The payoff function for a forwarder is defined as the companys profit and the clients payoff function as fee paid for forwarding services. To determine the influence of the demand parameters on the forwarders optimal strategies, the demand for transport services is represented as a flow of requests characterized by two numeric parameters delivery distance and consignment weight. Findings. The conducted experimental studies have shown that as a result of the use of the proposed methodology, the optimal strategy of a forwarding company can always be determined from the payoff matrix. The performed simulation experiment allowed us to state that in most cases the forwarders optimal strategy is mixed (the technological and commercial services should be provided with the given probability while servicing the flow of requests from freight owners). Originality. The studies on the influence of the request flow parameters on the probabilities of choosing the elementary strategies are carried in the paper for the first time. Practical value. The proposed methodology can be used as the basic tool for supporting decisions of freight forwarders while servicing the cargo owners at the market of road freight transportation.

show abstract

A Decision Support Tool for Urban Freight Transport Planning Based on a Multi-Objective Evolutionary Algorithm

Cited by 14 publications

References 46 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

A Robust Decision-Making Framework Based on Collaborative Agents

Choosing a servicing company’s strategy while interacting with freight owners at the road transport market

Contact Info

Product

Resources

About