Modeling and Planning Multimodal Transport Paths for Risk and Energy Efficiency Using AND/OR Graphs and Discrete Ant Colony Optimization

Wang, Zhanzhong; Zhang, Minghang; Chu, Ruijuan; Zhao, Liang

doi:10.1109/access.2020.3010376

Cited by 20 publications

(9 citation statements)

References 48 publications

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“…Since we deal with a combinatorial optimization problem, a GA is selected. It should be noted that some of the evolutionary algorithms, such as particle swarm optimization (PSO) or covariance matrix adaptation evolutionary strategies, are originally proposed for a continuous search space [49].…”

Section: B Spatial Objective Functionmentioning

confidence: 99%

IoT-Based Route Recommendation for an Intelligent Waste Management System

Ghahramani

Zhou

Mölter

et al. 2022

IEEE Internet Things J.

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The Internet of Things (IoT) is a paradigm characterized by a network of embedded sensors and services. These sensors are incorporated to collect various information, track physical conditions, e.g., waste bins' status, and exchange data with different centralized platforms. The need for such sensors is increasing; however, the proliferation of technologies comes with various challenges. For example, how can IoT and its associated data be used to enhance waste management? In smart cities, an efficient waste management system is crucial. Artificial intelligence (AI) and IoT-enabled approaches can empower cities to manage the waste collection. This work proposes an intelligent approach to route recommendation in an IoT-enabled waste management system given spatial constraints. It performs a thorough analysis based on AI-based methods and compare their corresponding results. Our solution is based on a multiple-level decision-making process in which bins' status and coordinates are taken into account to address the routing problem. Such AI-based models can help engineers design a sustainable infrastructure system.

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Section: B Spatial Objective Functionmentioning

confidence: 99%

IoT-Based Route Recommendation for an Intelligent Waste Management System

Ghahramani

Zhou

Mölter

et al. 2022

IEEE Internet Things J.

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“…-A multimodal transport path sequence: AND/OR graphs facilitate planning by Wang et al (2020b). It proposes a triple-phase generate route method for a feasible multimodal transport path sequence, based on AND/OR graphs.…”

Section: Multimodal Transport Planningmentioning

confidence: 99%

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

Matei¹,

Erdei²,

Pintea³

2021

Informatica

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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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“…-A multimodal transport path sequence: AND/OR graphs facilitate planning by [44]. It is proposed a triplephase generate route method for a feasible multimodal transport path sequence, based on AND/OR graphs.…”

Section: > Passenger and Freight Flows Planning Multimodal Transportmentioning

confidence: 99%

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

Matei,

Rudolf,

Pintea

2021

Preprint

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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 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.

show abstract

Modeling and Planning Multimodal Transport Paths for Risk and Energy Efficiency Using AND/OR Graphs and Discrete Ant Colony Optimization

Cited by 20 publications

References 48 publications

IoT-Based Route Recommendation for an Intelligent Waste Management System

IoT-Based Route Recommendation for an Intelligent Waste Management System

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

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

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