Multi-objective heterogeneous vehicle routing and scheduling problem with energy minimizing

Ghannadpour, Seyed Farid; Zarrabi, Abdolhadi

doi:10.1016/j.swevo.2018.08.012

Cited by 68 publications

(23 citation statements)

References 47 publications

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“…Satisfactory-GVRP (SGVRP) is also another concept that has been developed. In this concept, maximizing customer satisfaction is also becoming one of the main objectives [31,32]. GVRP can also be combined with scheduling problems in order to get a balanced environmental and economic costs by implementing effective vehicle routing and scheduling.…”

Section: Green Vehicle Routing Problemmentioning

confidence: 99%

Heterogeneous Fleet Green Vehicle Routing Problem: A Literature Review

Normasari

Lathifah

2021

Angkasa

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Transportation, as a part of the supply chain process, contributes to carbon emission which leads to climate change and global warming. This environmental issue gives an impact to decisions regarding the supply chain of a company. One way to deal with this issue is by analyzing their vehicle routing problem. In this study, the issue about routing problems in green supply chain by considering the heterogeneous fleet is being discussed. One variant of Green Vehicle Routing Problem (GVRP) reviewed in this paper is about Heterogeneous Alternative Fuel Vehicles for Green Vehicle Routing Problem (HAFVGVRP). The purpose of this study is to review the development of GVRP with heterogeneous alternative fuel vehicles and the gap or state-of-the-art on existing researches. The review was classified according to the objectives, type of fleet, and solution used. Moreover, this study also presents the trend and direction of further research.

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Section: Green Vehicle Routing Problemmentioning

confidence: 99%

Heterogeneous Fleet Green Vehicle Routing Problem: A Literature Review

Normasari

Lathifah

2021

Angkasa

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“…Em [12]é abordado o problema de roteamento de veículos heterogêneos (motocicletas e caminhões) em uma rede de distribuição de produtos. De maneira similar, [13] abordaram roteamento e scheduling de frotas heterogêneas com ACO. Em [14], [15] são reportados algoritmos híbridos entre fuzzy+ACO e AG+ACO para planejamento de rotas.…”

Section: Revisão Da Literaturaunclassified

Definição do Trajeto de um Robô Inspetor de Vasos de Pressão Esféricos Utilizando Otimização por Colônia de Formigas

Dalmedico¹,

Oliveira²,

Lopes³

2020

Anais Do 14. Congresso Brasileiro De Inteligência Computacional

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“…At present, the VRP is being developed to be better suited to conditions or terms that are close to reality, which makes the problem more complicated; for example, differences types of vehicles used [31,32], different vehicle speeds [37,38], congestion or different routes of transportation [39], considering weight or friction [40], and taking into account the use of sustainable resources [35]. From these points, it is inevitable that the VRP must be constantly developed.…”

Section: Literature Reviewmentioning

confidence: 99%

Modified Differential Evolution Algorithm for a Transportation Software Application

Supattananon

Akararungruangkul

2019

Journal of Open Innovation: Technology, Market, and Complexity

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This research developed a solution approach that is a combination of a web application and the modified differential evolution (MDE) algorithm, aimed at solving a real-time transportation problem. A case study involving an inbound transportation problem in a company that has to plan the direct shipping of a finished product to be collected at the depot where the vehicles are located is presented. In the newly designed transportation plan, a vehicle will go to pick up the raw material required by a certain production plant from the supplier to deliver to the production plant in a manner that aims to reduce the transportation costs for the whole system. The reoptimized routing is executed when new information is found. The information that is updated is obtained from the web application and the reoptimization process is executed using the MDE algorithm developed to provide the solution to the problem. Generally, the original DE comprises of four steps: (1) randomly building the initial set of the solution, (2) executing the mutation process, (3) executing the recombination process, and (4) executing the selection process. Originally, for the selection process in DE, the algorithm accepted only the better solution, but in this paper, four new selection formulas are presented that can accept a solution that is worse than the current best solution. The formula is used to increase the possibility of escaping from the local optimal solution. The computational results show that the MDE outperformed the original DE in all tested instances. The benefit of using real-time decision-making is that it can increase the company’s profit by 5.90% to 6.42%.

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Multi-objective heterogeneous vehicle routing and scheduling problem with energy minimizing

Cited by 68 publications

References 47 publications

Heterogeneous Fleet Green Vehicle Routing Problem: A Literature Review

Heterogeneous Fleet Green Vehicle Routing Problem: A Literature Review

Definição do Trajeto de um Robô Inspetor de Vasos de Pressão Esféricos Utilizando Otimização por Colônia de Formigas

Modified Differential Evolution Algorithm for a Transportation Software Application

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