A Self-adapting Immigrational Genetic Algorithm for Solving a Real-Life Application of Vehicle Routing Problem

Petrovan, Adrian; Erdei, Rudolf; Pop, Petrică C.; Matei, Oliviu

doi:10.1007/978-3-030-31362-3_15

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…The article describes the advantages of the immigrational approach on the overall quality of the algorithm (result quality and run-time speed). Diverse versions of the Genetic Algorithms for solving the current problem are presented by Matei and Pop (2010) and Petrovan et al (2019). Ant colony methods were used to solve Generalized VRP by Pop et al (2009aPop et al ( , 2009b and Pintea et al (2011).…”

Section: Models and Solvers: (G)vrp For Further Multimodal Extensionmentioning

confidence: 99%

Selective Survey: Most Efficient Models and Solvers for Integrative Multimodal Transport

Matei¹,

Erdei²,

Pintea³

2021

Informatica

Self Cite

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In the family of Intelligent Transportation Systems (ITS), Multimodal Transport Systems (MMTS) have placed themselves as a mainstream transportation mean of our time as a feasible integrative transportation process. The Global Economy progressed with the help of transportation. The volume of goods and distances covered have doubled in the last ten years, so there is a high demand of an optimized transportation, fast but with low costs, saving resources but also safe, with low or zero emissions. Thus, it is important to have an overview of existing research in this field, to know what has already been done and what is to be studied next. The main objective is to explore a beneficent selection of the existing research, methods and information in the field of multimodal transportation research, to identify industry needs and research gaps and provide context for future research. The selective survey covers multimodal transport design and optimization in terms of: cost, time, and network topology. The multimodal transport theoretical aspects, context and resources are also covering various aspects. The survey's selection includes currently existing best methods and solvers for Intelligent Transportation Systems (ITS). The gap between theory and real-world applications should be further solved in order to optimize the global multimodal transportation system.

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Section: Models and Solvers: (G)vrp For Further Multimodal Extensionmentioning

confidence: 99%

Selective Survey: Most Efficient Models and Solvers for Integrative Multimodal Transport

Matei¹,

Erdei²,

Pintea³

2021

Informatica

Self Cite

View full text Add to dashboard Cite

show abstract

“…The article describes the advantages of the immigrational approach on the overall quality of the algorithm (result quality and run-time speed). Diverse versions Genetic Algorithms for solving the current problem are presented by [91] and [92]. Ant colony methods were used to solve Generalized VRP by [93], [94] and [95].…”

Section: Future Possible Extensions From Unimodal To Multimodal Trans...mentioning

confidence: 99%

Selective Survey: Most Efficient Models and Solvers for Integrative Multimodal Transport

Matei,

Rudolf,

Pintea

2021

Preprint

Self Cite

View full text Add to dashboard Cite

In the family of Intelligent Transportation Systems (ITS), Multimodal Transport Systems (MMTS) have placed themselves as a mainstream transportation mean of our time as a feasible integrative transportation process. The Global Economy progressed with the help of transportation. The volume of goods and distances covered have doubled in the last ten years, so there is a high demand of an optimized transportation, fast but with low costs, saving resources but also safe, with low or zero emissions. Thus, it is important to have an overview of existing research in this field, to know what was already done and what is to be studied next. The main objective is to explore a beneficent selection of the existing research, methods and information in the field of multimodal transportation research, to identify industry needs and gaps in research and provide context for future research. The selective survey covers multimodal transport design and optimization in terms of: cost, time, and network topology. The multimodal transport theoretical aspects, context and resources are also covering various aspects. The survey's selection includes nowadays best methods and solvers for Intelligent Transportation Systems (ITS). The gap between theory and real-world applications should be further solved in order to optimize the global multimodal transportation system.

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Genetic Algorithm for a Non-standard Complex Problem of Partitioning and Vehicle Routing

Erdei

Delinschi

Matei

2023

Lecture Notes in Networks and Systems

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A Self-adapting Immigrational Genetic Algorithm for Solving a Real-Life Application of Vehicle Routing Problem

Cited by 4 publications

References 16 publications

Selective Survey: Most Efficient Models and Solvers for Integrative Multimodal Transport

Selective Survey: Most Efficient Models and Solvers for Integrative Multimodal Transport

Selective Survey: Most Efficient Models and Solvers for Integrative Multimodal Transport

Genetic Algorithm for a Non-standard Complex Problem of Partitioning and Vehicle Routing

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