Robust multimodal hub network design for hazmat considering a detour strategy

Routing and scheduling decisions in the hierarchical hub location problem

Population-based risk equilibration for the multimode hazmat transport network design problem

A monetary network cost problem involving a homogeneous multi-level tree of processors and links is discussed. The monetary network cost of processing a divisible load, which is linearly dependent on the amount of divisible workload, is basically composed of a communication cost and a computing cost. A monetary network analysis is performed by aggregating the network speed parameters and network cost parameters. This allows one to obtain a closed form solution for the total monetary network cost with maintaining a minimum total parallel processing finish time. Through a mathematical derivation of the ratio of total computing time variation to total network cost variation against changes in network size, insights on trends of network performance against network cost are achieved.

Organic-waste-derived butyric acid-to-biodiesel supply-chain network: Strategic planning design using a deterministic snapshot model

Large-scale multimodal transportation network models and algorithms-Part II: Network capacity and network design problem

In order to solve the challenges brought by multi-source and cross-domain scenarios to online music education, this paper designs an online music education system based on advanced artificial intelligence technology, which can provide personalized learning course resource recommendations for music online learners. The system includes four layers, consisting of user interface layer, application module layer, function module layer and data storage layer. At the application module level, this paper proposes a music recommendation algorithm based on a personalized multimodal network model. The recommendation algorithm performs music information retrieval (MIR) based on the similarity judgment of the contour of music pitch and the overall change, and constructs a multimodal network model based on the user’s preference for resources to achieve personalized music recommendation. This paper crawls more than one million music score data from a well-known music platform database in China to establish a dataset to evaluate the performance of this method. The comparison results with three existing works show that the method proposed in this paper has good performance and can provide users with suitable music recommendations. The artificial intelligence technology-driven online music education mechanism proposed in this paper has good prospects.

Capital and total cost targets for mass exchange networks: Part 1: Simple capital cost models

The integration of multiple resources conservation networks is necessary to attain the ever-stringent sustainable goals. This work takes initiatives to develop a heat integrated water network via a proposed P-graph-based sequential methodology. In the first step, a set of feasible water regeneration networks is generated using the conventional P-graph framework. Then, the obtained feasible networks will be used as the inputs in the second stage which aims to generate various sets of feasible heat exchanger networks. It is worth noting that the second model is solved by an extended P-graph framework (P-HENS) for combinatorial process network optimization. The solutions are then ranked based on the total network cost. To demonstrate the effectiveness of the proposed method, a typical water regeneration network (three sources and three sinks) with multi-contaminants is used. The results show a total of 103 feasible water network structures (water network cost ranging from 0.76 M$/y to 1.18 M$/y). Thereafter, a list of feasible HIWRN can be determined using P-HENS. The top four HIWRNs which offer similar total network cost (~1.639 M$/y) are demonstrated. This proposed method provides valuable insights that allow decision-makers to further select the optimal solution which may be more beneficial as compared to the one obtained via conventional methods.

Virtual network functions (VNFs) are placed across the network to complete the required network performance of virtual network slice (vNS), and the placement of VNFs is flexible and problematic. Besides, a VNF can be decomposed into multiple sub-functions, and the same type of sub-function can be re-used by multiple VNFs. Therefore, the resources of subfunctions in different vNS requests can be shared and the cost of the substrate network is reduced. So, function decomposition makes the VNF placement problem more flexible and challenging. In this paper, we study the VNF placement problem with function decomposition for vNS, and formulate it as an integer linear programming (ILP) aiming to minimize the total cost of the substrate network. Then, an approach named Placement algorithm based on Function Decomposition (P-FD) is proposed to get a near-optimal solution of this problem. Finally, simulation results show that P-FD can achieve less total cost compared with algorithms in existing.

Shipment scheduling in hub location problems

A multiobjective hub-airport location problem for an airline network design

We propose a comprehensive scalable algorithm simultaneously assessing the routing, scheduling and virtualization in Time-Domain Wavelength Interleaved Network (TWIN). TWIN is an energy-efficient optical burst switching technology for metropolitan area and data center intra- and interconnections, with destinations using separate allocated sets of wavelengths for the reception. Given the costs of the optical transponders and the wavelength use per km of fiber length, the proposed algorithm solves the routing and wavelength assignment problem, and in the same time allocates the time slots to traffic flows (performs the slot scheduling), so that the total network cost is minimized. The algorithm also enables the construction of overlayed virtual networking domains at minimum cost, which share the transponders and network links, and can employ different scheduling policies. The performance of the algorithm is compared with the pre-existing optimal dimensioning solution for single virtualization domain based on Integer Linear Programing, for different scenarios. The obtained results show that the network cost is within 27% of the optimal.

Connectivity of the human insula: A cortico-cortical evoked potential (CCEP) study

In this paper the authors study a logistics hub location problem in which the network could not be formed as a full interconnected hub-level network because of the investment restrictions. Nevertheless, the hubs to be located must form a set of interconnecting lines. Logistics hubs can be connected with highly efficient pathways, enabling economies of scale to be achieved on the transportation cost (or transport time) between hubs. The objective is to minimize the total weighted transport time between all pairs of nodes while considering the logistics operation time taken on each key connected component of the network. Besides, a budget constraint on the total set-up cost of the hub network is also taken into account. A mathematical model is presented to solve the hub line location problem (HLLP) through pure integer nonlinear programming (PINLP). Numerical results on a test case confirms the validity of the proposed PINLP model and indicates the impact of the budget constraint on the topology of the network.

Increased hazmat transportation and its undesirable effects have governments and researchers have special focus on this problem. Various aspects of this field have been studied, and most of them have tried to reduce the total risk, travel time and costs. In this study, we assume stops in the intermediate nodes are allowed because stops en route as a short break may reduce the risk of the trip. The proposed model mainly selects the best facility to assign to customer, finds the optimal route to serve the customers, and determines schedule for arrival and departure time from nodes. Given that the proposed model is NP-hard, a NSGA-II is used to solve it. In order to evaluate the efficiency of the algorithm, a real case of fossil fuels distribution in IRAN is implemented. The computational results show that the proposed algorithm is an efficient algorithm to achieve near-optimal solutions for the medium and large-scale problems.