scholarly journals Minimize Traffic Congestion: An Application of Maximum Flow in Dynamic Networks

2012 ◽  
Vol 8 (1) ◽  
pp. 63-74
Author(s):  
K. Kaanodiya ◽  
Mohd Rizwanullah
Keyword(s):  
Traffic Congestion ◽  
Optimization Problem ◽  
Supply And Demand ◽  
Dynamic Networks ◽  
Dynamic Network ◽  
Maximum Flow ◽  
Transport Services ◽  
Long Time ◽  
Large Product ◽  
Dynamic Version

Minimize Traffic Congestion: An Application of Maximum Flow in Dynamic NetworksAn important characteristic of a network is its capacity to carry flow. What, given capacities on the arcs, is the maximum flow that can be sent between any two nodes? The dynamic version of the maximum flow problem on networks that generalizes the well-known static one. This basic combinatorial optimization problem has a large implementation for many practical problems. Traffic congestion is a consequence of the nature of supply and demand: capacity is time consuming and costly to build and is fixed for long time periods, demand fluctuates over time, and transport services cannot be stored to smooth imbalances between capacity and demand. In this paper, I tried to solve the traffic congestion problem i.e. Maximum flow of goods in a dynamic network with the help of a Lingo Model. The same can be generalized for the large product if the software supports the systems.

scholarly journals DNA-based constitutional dynamic networks as functional modules for logic gates and computing circuit operations

2021 ◽  
Vol 12 (15) ◽  
pp. 5473-5483
Author(s):  
Zhixin Zhou ◽  
Jianbang Wang ◽  
R. D. Levine ◽  
Francoise Remacle ◽  
Itamar Willner
Keyword(s):  
Nucleic Acid ◽  
Dynamic Networks ◽  
Dynamic Network ◽  
Logic Gates ◽  
Functional Modules ◽  
Logic Operations

A nucleic acid-based constitutional dynamic network (CDN) provides a single functional computational module for diverse input-guided logic operations and computing circuits.

scholarly journals A framework for IoT-enabled environment aware traffic management

2021 ◽  
Vol 11 (1) ◽  
pp. 518
Author(s):  
Mohamed Fazil Mohamed Firdhous ◽  
B. H. Sudantha ◽  
Naseer Ali Hussien
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Traffic Management ◽  
Fine Particles ◽  
Environment Pollution ◽  
Negative Effects ◽  
Traffic Condition ◽  
Pollution Levels ◽  
Transport Services ◽  
The Cost

Vehicular traffic has increased across all over the world especially in urban areas due to many reasons including the reduction in the cost of vehicles, degradation of the quality of public transport services and increased wealth of people. The traffic congestion created by these vehicles causes many problems. Increased environment pollution is one of the most serious negative effects of traffic congestion. Noxious gases and fine particles emitted by vehicles affect people in different ways depending on their age and present health conditions. Professionals and policy makers have devised schemes for better managing traffic in congested areas. These schemes suffer from many shortcomings including the inability to adapt to dynamic changes of traffic patterns. With the development of technology, new applications like Google maps help drivers to select less congested routes. But, the identification of the best route takes only the present traffic condition on different road segments presently. In this paper the authors propose a system that helps drivers select routes based on the present and expected environment pollution levels at critical points in a given area.

scholarly journals Supply Chain Management and the Covid-19 Outbreak: Optimizing its Role for Indonesia

2020 ◽  
Vol 3 (2) ◽  
pp. 196-202
Author(s):  
Siti Amalia ◽  
Dio Caisar Darma ◽  
Siti Maria
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Supply Chains ◽  
Supply And Demand ◽  
Chain Model ◽  
Chain Management ◽  
New Normal ◽  
Food Supply Chains ◽  
Long Time ◽  
Demand Patterns

At the beginning of the emergence of Covid-19, there was panic buying in Indonesia which caused an unusual situation in supply management. Although the handling of this epidemic has entered a "new normal", the availability of stocks of electronics, automotive, pharmaceuticals, food, and others is running low and out of control, so supply chain management is needed. The purpose of this article is to try to see the extent of the transformation in supply and demand in Indonesia. With this in-depth literature, the supply chain model is likely to transform globally, given that many companies are confused about management being unable to cope with drastic changes in the market. The demand patterns over the past period indicate a shift from offline to online storefronts. Even though it has now entered a transition to a new normal and shopping outlets are slowly opening up, online shopping or demand patterns are predicted to last a long time. Therefore, supply chain actors, especially farmers, logistics entrepreneurs, and shipping services, inevitably have to be able to quickly adapt to changing patterns in Indonesia. There is an imbalance between the demand and supply sides. Food supply chains tend to be unique in comparison to the supply chains of other products and services.

scholarly journals Air Freight Transport Developments in Bulgaria – Trends and Perspectives

2021 ◽  
Vol 27 (3) ◽  
pp. 18-36
Keyword(s):  
Swot Analysis ◽  
Necessary Conditions ◽  
Supply And Demand ◽  
Freight Transport ◽  
Commodity Markets ◽  
Transport Services ◽  
Delivery Times ◽  
Freight Traffic ◽  
Rapid Pace ◽  
Air Freight

Air transport is developing at a rapid pace globally and is of particular importance for the mobility of people and goods. Through its flexibility, it responds to the ever-changing situation in commodity markets and provides the necessary conditions for transport services’ supply and demand in shortening the delivery times. The main subject of analysis in the presented article is the development of air freight transport over the last 12 years. The main results of the analysis of the volumes and changes of freight traffic to and from Bulgarian airports, as well as carried by the main carriers, give the grounds for SWOT analysis and is used to outline the main prospects for the future of air freight transport. The main objective of the survey presented is to outline trends for the development of air freight transport in the country and in particular to clarify the various factors influencing the demand for freight transport by identifying a system of indicators measuring the freight volumes and the loading work carried out, which can be analyzed regularly, and which allows the forecasting of changes in freight volumes during certain periods of time.

An experimental evaluation and guideline for path finding in weighted dynamic network

2021 ◽  
Vol 14 (11) ◽  
pp. 2127-2140
Author(s):  
Mengxuan Zhang ◽  
Lei Li ◽  
Xiaofang Zhou
Keyword(s):  
Shortest Path ◽  
State Of The Art ◽  
Dynamic Networks ◽  
Real Life ◽  
Dynamic Network ◽  
Problem Space ◽  
Network Applications ◽  
Complete Problem ◽  
Path Computation ◽  
Shortest Path Computation

Shortest path computation is a building block of various network applications. Since real-life networks evolve as time passes, the Dynamic Shortest Path (DSP) problem has drawn lots of attention in recent years. However, as DSP has many factors related to network topology, update patterns, and query characteristics, existing works only test their algorithms on limited situations without sufficient comparisons with other approaches. Thus, it is still hard to choose the most suitable method in practice. To this end, we first identify the determinant dimensions and constraint dimensions of the DSP problem and create a complete problem space to cover all possible situations. Then we evaluate the state-of-the-art DSP methods under the same implementation standard and test them systematically under a set of synthetic dynamic networks. Furthermore, we propose the concept of dynamic degree to classify the dynamic environments and use throughput to evaluate their performance. These results can serve as a guideline to find the best solution for each situation during system implementation and also identify research opportunities. Finally, we validate our findings on real-life dynamic networks.

Money metrology

2020 ◽  
pp. 42-50
Author(s):  
V. N. Krutikov ◽  
V. V. Okrepilov
Keyword(s):  
Gold Standard ◽  
Supply And Demand ◽  
Precious Metals ◽  
Legal Metrology ◽  
Important Principle ◽  
Monetary System ◽  
Stage Of Development ◽  
Fixed Weight ◽  
Long Time ◽  
Material Measure

The influence of the provisions of legal metrology on the formation and functioning of the monetary environment in market conditions is studied. It is shown that the use of material (reference) measures for determining the value of goods in monetary units makes it possible to form a stable monetary system, equal for all market participants. This system can reasonably be attributed to information measuring systems. Systems based on the use of constant material measures that determine the value of goods and money in international trade have been formed and functioned for a long time. In the XIX-XX centuries, the monetary system, in which a fixed weight of gold served as the material measure of money, was called the “gold standard”. In the 1970s, this system was abandoned without objective reasons. Nowadays, many people believe that the main reason is the uncontrolled issuance of paper money (US dollars). As a result, the material measure of money was replaced by a monetary measure. The money of a number of selected countries turned out to be a measure of the national currencies of other countries. Then money was made a commodity – an object of market trading, the price of which is determined by supply and demand. Thus, the most important principle of metrology was violated – the invariability (constancy) of the measure of system objects. The resulting monetary system became unstable. This situation has led to an increase in the number of proposals for a return to the gold standard. The analysis carried out in the paper confirmed the relevance of these proposals. At the present stage of development of metrology, it is advisable to explore the possibility of a broader (not only at the expense of precious metals) resource provision of material monetary measures, in particular, to consider the possibility of using materials and (or) goods that are in high demand in the international market as monetary measures.

Data Mining Techniques for Communities’ Detection in Dynamic Social Networks

Data Mining ◽  
2013 ◽  
pp. 719-733
Author(s):  
Céline Robardet
Keyword(s):  
Dynamic Networks ◽  
Dynamic Network ◽  
Added Value ◽  
Strong Interactions ◽  
Time Stamp ◽  
Efficient Computation ◽  
Real World Data ◽  
Positive Side ◽  
Dynamic Social Networks ◽  
Temporal Events

Social network analysis studies relationships between individuals and aims at identifying interesting substructures such as communities. This type of network structure is intuitively defined as a subset of nodes more densely linked, when compared with the rest of the network. Such dense subgraphs gather individuals sharing similar property depending on the type of relation encoded in the graph. In this chapter we tackle the problem of identifying communities in dynamic networks where relationships among entities evolve over time. Meaningful patterns in such structured data must capture the strong interactions between individuals but also their temporal relationships. We propose a pattern discovery method to identify evolving patterns defined by constraints. In this paradigm, constraints are parameterized by the user to drive the discovery process towards potentially interesting patterns, with the positive side effect of achieving a more efficient computation. In the proposed approach, dense and isolated subgraphs, defined by two user-parameterized constraints, are first computed in the dynamic network restricted at a given time stamp. Second, the temporal evolution of such patterns is captured by associating a temporal event types to each subgraph. We consider five basic temporal events: the formation, dissolution, growth, diminution and stability of subgraphs from one time stamp to the next one. We propose an algorithm that finds such subgraphs in a time series of graphs processed incrementally. The extraction is feasible thanks to efficient pruning patterns strategies. Experimental results on real-world data confirm the practical feasibility of our approach. We evaluate the added-value of the method, both in terms of the relevancy of the extracted evolving patterns and in terms of scalability, on two dynamic sensor networks and on a dynamic mobility network.

Identifying influential nodes in dynamic social networks based on degree-corrected stochastic block model

2016 ◽  
Vol 30 (16) ◽  
pp. 1650092 ◽  
Author(s):  
Tingting Wang ◽  
Weidi Dai ◽  
Pengfei Jiao ◽  
Wenjun Wang
Keyword(s):  
Social Networks ◽  
Real World ◽  
Dynamic Networks ◽  
Dynamic Network ◽  
Community Structures ◽  
Block Model ◽  
Real World Data ◽  
Stochastic Block Model ◽  
Dynamic Social Networks ◽  
Influential Nodes

Many real-world data can be represented as dynamic networks which are the evolutionary networks with timestamps. Analyzing dynamic attributes is important to understanding the structures and functions of these complex networks. Especially, studying the influential nodes is significant to exploring and analyzing networks. In this paper, we propose a method to identify influential nodes in dynamic social networks based on identifying such nodes in the temporal communities which make up the dynamic networks. Firstly, we detect the community structures of all the snapshot networks based on the degree-corrected stochastic block model (DCBM). After getting the community structures, we capture the evolution of every community in the dynamic network by the extended Jaccard’s coefficient which is defined to map communities among all the snapshot networks. Then we obtain the initial influential nodes of the dynamic network and aggregate them based on three widely used centrality metrics. Experiments on real-world and synthetic datasets demonstrate that our method can identify influential nodes in dynamic networks accurately, at the same time, we also find some interesting phenomena and conclusions for those that have been validated in complex network or social science.

scholarly journals The (T, L)-Path Model and Algorithms for Information Dissemination in Dynamic Networks

Information ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 212
Author(s):  
Zhiwei Yang ◽  
Weigang Wu
Keyword(s):  
Network Topology ◽  
Information Dissemination ◽  
Dynamic Networks ◽  
Dynamic Network ◽  
Network Models ◽  
Point Of View ◽  
Path Model ◽  
Dynamic Network Models ◽  
Topology Changes ◽  
Practical Design

A dynamic network is the abstraction of distributed systems with frequent network topology changes. With such dynamic network models, fundamental distributed computing problems can be formally studied with rigorous correctness. Although quite a number of models have been proposed and studied for dynamic networks, the existing models are usually defined from the point of view of connectivity properties. In this paper, instead, we examine the dynamicity of network topology according to the procedure of changes, i.e., how the topology or links change. Following such an approach, we propose the notion of the “instant path” and define two dynamic network models based on the instant path. Based on these two models, we design distributed algorithms for the problem of information dissemination respectively, one of the fundamental distributing computing problems. The correctness of our algorithms is formally proved and their performance in time cost and communication cost is analyzed. Compared with existing connectivity based dynamic network models and algorithms, our procedure based ones are definitely easier to be instantiated in the practical design and deployment of dynamic networks.

scholarly journals Dynamic network prediction

2020 ◽  
Vol 8 (4) ◽  
pp. 574-595
Author(s):  
Ravi Goyal ◽  
Victor De Gruttola
Keyword(s):  
Social Relationships ◽  
Network Structure ◽  
Broad Class ◽  
Dynamic Networks ◽  
Dynamic Network ◽  
Simulation Studies ◽  
Population Composition ◽  
Statistical Framework ◽  
Network Properties ◽  
Network Prediction

AbstractWe present a statistical framework for generating predicted dynamic networks based on the observed evolution of social relationships in a population. The framework includes a novel and flexible procedure to sample dynamic networks given a probability distribution on evolving network properties; it permits the use of a broad class of approaches to model trends, seasonal variability, uncertainty, and changes in population composition. Current methods do not account for the variability in the observed historical networks when predicting the network structure; the proposed method provides a principled approach to incorporate uncertainty in prediction. This advance aids in the designing of network-based interventions, as development of such interventions often requires prediction of the network structure in the presence and absence of the intervention. Two simulation studies are conducted to demonstrate the usefulness of generating predicted networks when designing network-based interventions. The framework is also illustrated by investigating results of potential interventions on bill passage rates using a dynamic network that represents the sponsor/co-sponsor relationships among senators derived from bills introduced in the U.S. Senate from 2003 to 2016.

Sign in / Sign up

Export Citation Format

Share Document