An Optimal Allocation Method of Power Multimodal Network Resources Based on NSGA-II

Basic services for power business were provided by the power multimodel network providers. However, because the power multimodal network is usually complex and changeable, the service of power business is often unstable. This problem can be solved by a suitable network resource optimization method. Therefore, how to design a network resource optimization method that seeks a compromise between multiple performance indicators that achieve the normal operation of power multimode networks is still extremely challenging. An optimal allocation method of power multimodal network resources based on NSGA-II was proposed by this paper. Firstly, the power multimodal network-resource model is established, and the problems existing in the resource optimization process are analyzed. Secondly, preprocessing technology and indirect coding technology are applied to NSGA-II, which solves the coding problem and convergence problem of the application of genetic algorithm to the optimization of network resource allocation. Finally, the simulation results show that, compared with the control algorithm, this method has further optimized the various indicators of the resource allocation of the power multimodal network, and the performance has been improved by more than 6%.

Multimodal Network Architecture for Shared Situational Awareness Amongst Vessels

To shift the paradigm towards Industry 4.0, maritime domain aims to utilize shared situational awareness (SSA) amongst vessels. SSA entails sharing various heterogeneous information, depending on the context and use case at hand, and no single wireless technology is equally suitable for all uses. Moreover, different vessels are equipped with different hardware and have different communication capabilities, as well as communication needs. To enable SSA regardless of the vessel’s communication capabilities and context, we propose a multimodal network architecture that utilizes all of the network interfaces on a vessel, including multiple IEEE 802.11 interfaces, and automatically bootstraps the communication transparently to the applications, making the entire communication system environment-aware, service-driven, and technology-agnostic. This paper presents the design, implementation, and evaluation of the proposed network architecture which introduces virtually no additional delays as compared to the Linux communication stack, automates communication bootstrapping, and uses a novel application-network integration concept that enables application-aware networks, as well as network-aware applications. The evaluation was conducted for several IEEE 802.11 flavors. Although inspired by SSA for vessels, the proposed architecture incorporates several concepts applicable in other domains. It is modular enough to support existing, as well as emerging communication technologies.

Assessing road pricing effects on a multimodal network based on macroscopic fundamental diagram hysteresis

Purpose Road pricing is an efficient strategy for managing urban traffic to relieve congestion. The macroscopic fundamental diagram (MFD), which relates the average network density and flow, is a simple tool for assessing road pricing effects on transportation network performance. However, recent research indicates that it may have complexity (an MFD hysteresis loop), especially for city-scale networks. Although ignoring MFD hysteresis may provide inaccurate results, pricing models that consider this hysteresis are scarce. This paper aims to assess road pricing effects on network performance considering MFD hysteresis characteristics. Design/methodology/approach This paper evaluated different pricing strategies spatially and temporally and compared network performance based on MFD shape in the presence of MFD hysteresis loops. These strategies were developed on a multimodal (cars and buses) network using a multi-agent transport simulation (MATSim). Findings This study found that pricing some links for a short duration with an optimum charge calculated based on the MFD provides higher travel time savings than the previous relevant studies. Originality/value These findings may facilitate assessing road pricing effects on multimodal network performance considering MFD hysteresis.

Supernetwork Representation Formulation of a Multiclass Simultaneous Transportation Equilibrium Model as a Fixed Demand User Equilibrium Problem

A multiclass simultaneous transportation equilibrium model (MSTEM) explicitly distinguishes between different user classes in terms of socioeconomic attributes, trip purpose, pure and combined transportation modes, as well as departure time, all interacting over a physically unique multimodal network. It enhances the prediction process behaviorally by combining the trip generation and departure time choices to trip distribution, modal split, and trip assignment choices in a unified and flexible framework that has many advantages from both supply and demand sides. However, the development of this concept of multiple classes increases the mathematical complexity of travel forecasting models. In this research, the authors reduce this mathematical complexity by using the supernetwork representation formulation of the diagonalized MSTEM as a fixed demand user equilibrium (FDUE) problem.