Multi-itinerary optimization as cloud service

2021 ◽  
Vol 64 (11) ◽  
pp. 121-129
Author(s):  
Alexandru Cristian ◽  
Luke Marshall ◽  
Mihai Negrea ◽  
Flavius Stoichescu ◽  
Peiwei Cao ◽  
...  
Keyword(s):  
Travel Time ◽  
Time Windows ◽  
Algorithm Design ◽  
Cloud Service ◽  
Multiple Agents ◽  
Solution Quality ◽  
Traffic Conditions ◽  
Time Distance ◽  
And Performance ◽  
Vehicle Capacity

In this paper, we describe multi-itinerary optimization (MIO)---a novel Bing Maps service that automates the process of building itineraries for multiple agents while optimizing their routes to minimize travel time or distance. MIO can be used by organizations with a fleet of vehicles and drivers, mobile salesforce, or a team of personnel in the field, to maximize workforce efficiency. It supports a variety of constraints, such as service time windows, duration, priority, pickup and delivery dependencies, and vehicle capacity. MIO also considers traffic conditions between locations, resulting in algorithmic challenges at multiple levels (e.g., calculating time-dependent travel-time distance matrices at scale and scheduling services for multiple agents). To support an end-to-end cloud service with turnaround times of a few seconds, our algorithm design targets a sweet spot between accuracy and performance. Toward that end, we build a scalable approach based on the ALNS metaheuristic. Our experiments show that accounting for traffic significantly improves solution quality: MIO finds efficient routes that avoid late arrivals, whereas traffic-agnostic approaches result in a 15% increase in the combined travel time and the lateness of an arrival. Furthermore, our approach generates itineraries with substantially higher quality than a cutting-edge heuristic (LKH), with faster running times for large instances.

scholarly journals APLIKASI ALGORITME BRANCH AND BOUND DALAM MODEL OPTIMISASI ROBUST

2019 ◽  
Vol 8 (4) ◽  
pp. 285
Author(s):  
LAILATUL RIZKIANA ◽  
NI KETUT TARI TASTRAWATI ◽  
NI LUH PUTU SUCIPTAWATI
Keyword(s):  
Robust Optimization ◽  
Travel Time ◽  
Branch And Bound ◽  
Optimization Problems ◽  
Branch And Bound Algorithm ◽  
Tourist Attraction ◽  
Traffic Conditions ◽  
Uncertainty Set ◽  
Time Distance ◽  
The Many

Bali is one of the regions in Indonesia which is famous for its tourism. Vacationing in Bali seems to be a must for every tourist, both domestic and foreign tourists. For tourists who are on vacation many things are considered be it time, distance, cost and others. Travel time with a distance that is already known is something that can not be estimated with certainty, given the many factors that influence including traffic conditions, weather, or road infrastructure. Robust optimization is one area of ??optimization that solves problems with uncertainty which in this study uses a box uncertainty set approach. Optimization problems can be solved by a branch and bound algorithm, the results obtained in the form of tourist attraction routes should be chosen with a minimum time and influenced by indefinite factors.

scholarly journals A model for the time dependent vehicle routing problem with time windows under traffic conditions with intelligent travel times

2021 ◽  
Author(s):  
Saeed Khanchehzarrin ◽  
Maral Shahmizad ◽  
Iraj Mahdavi ◽  
Nezam Mahdavi-Amiri ◽  
Peiman Ghasemi
Keyword(s):  
Travel Time ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
Time Windows ◽  
Time Dependent ◽  
Mixed Integer ◽  
Travel Times ◽  
Routing Problem ◽  
Traffic Conditions

A new mixed-integer nonlinear programming model is presented for the time-dependent vehicle routing problem with time windows and intelligent travel times. The aim is to minimize fixed and variable costs, with the assumption that the travel time between any two nodes depends on traffic conditions and is considered to be a function of vehicle departure time. Depending on working hours, the route between any two nodes has a unique traffic parameter. We consider each working day to be divided into several equal and large intervals, termed as a scenario. Here, allowing for long distances between some of the nodes, travel time may take more than one scenario, resulting in resetting the scenario at the start of each large interval. This repetition of scenarios has been used in modeling and calculating travel time. A tabu search optimization algorithm is devised for solving large problems. Also, after linearization, a number of random instances are generated and solved by the CPLEX solver of GAMS to assess the effectiveness of our proposed algorithm. Results indicate that the initial travel time is estimated appropriately and updated properly in accordance with to the repeating traffic conditions.

A method of obtaining P and S travel-time curves within a “Stripped Earth”*

1952 ◽  
Vol 42 (4) ◽  
pp. 313-314
Author(s):  
V. C. Stechschulte
Keyword(s):  
Travel Time ◽  
Depth Distribution ◽  
Epicentral Distance ◽  
Travel Times ◽  
Depth Of Focus ◽  
Distance Curve ◽  
Simple Method ◽  
Time Distance ◽  
Deep Focus

Abstract A simple method is outlined for obtaining from a time-distance curve of a deep-focus earthquake a table of travel times within an earth “stripped” to the depth h, the depth of focus. The method depends on the fact that such a curve for a deep-focus earthquake has a point of inflection and therefore has the same slope at two different values of epicentral distance. The Herglotz-Wiechert method may then be applied to these travel times to obtain a velocity-depth distribution.

scholarly journals Adaptive Secure Cross-Cloud Data Collaboration with Identity-Based Cryptography and Conditional Proxy Re-Encryption

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Qinlong Huang ◽  
Yue He ◽  
Wei Yue ◽  
Yixian Yang
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Security And Privacy ◽  
Broadcast Encryption ◽  
Cloud Data ◽  
Identity Based ◽  
Identity Based Cryptography ◽  
And Performance ◽  
Cryptographic Techniques ◽  
Data Collaboration

Data collaboration in cloud computing is more and more popular nowadays, and proxy deployment schemes are employed to realize cross-cloud data collaboration. However, data security and privacy are the most serious issues that would raise great concerns from users when they adopt cloud systems to handle data collaboration. Different cryptographic techniques are deployed in different cloud service providers, which makes cross-cloud data collaboration to be a deeper challenge. In this paper, we propose an adaptive secure cross-cloud data collaboration scheme with identity-based cryptography (IBC) and proxy re-encryption (PRE) techniques. We first present a secure cross-cloud data collaboration framework, which protects data confidentiality with IBC technique and transfers the collaborated data in an encrypted form by deploying a proxy close to the clouds. We then provide an adaptive conditional PRE protocol with the designed full identity-based broadcast conditional PRE algorithm, which can achieve flexible and conditional data re-encryption among ciphertexts encrypted in identity-based encryption manner and ciphertexts encrypted in identity-based broadcast encryption manner. The extensive analysis and experimental evaluations demonstrate the well security and performance of our scheme, which meets the secure data collaboration requirements in cross-cloud scenarios.

scholarly journals Modeling Operational Performance of Urban Roads with Heterogeneous Traffic Conditions

2021 ◽  
Author(s):  
Swapneel R. Kodupuganti ◽  
Sonu Mathew ◽  
Srinivas S. Pulugurtha
Keyword(s):  
North Carolina ◽  
Travel Time ◽  
Queue Length ◽  
Simulation Software ◽  
Heterogeneous Traffic ◽  
Operational Performance ◽  
Travel Time Reliability ◽  
Traffic Conditions ◽  
Vehicle Delay ◽  
Blue Line

The rapid growth in population and related demand for travel during the past few decades has had a catalytic effect on traffic congestion, air quality, and safety in many urban areas. Transportation managers and planners have planned for new facilities to cater to the needs of users of alternative modes of transportation (e.g., public transportation, walking, and bicycling) over the next decade. However, there are no widely accepted methods, nor there is enough evidence to justify whether such plans are instrumental in improving mobility of the transportation system. Therefore, this project researches the operational performance of urban roads with heterogeneous traffic conditions to improve the mobility and reliability of people and goods. A 4-mile stretch of the Blue Line light rail transit (LRT) extension, which connects Old Concord Rd and the University of North Carolina at Charlotte’s main campus on N Tryon St in Charlotte, North Carolina, was considered for travel time reliability analysis. The influence of crosswalks, sidewalks, trails, greenways, on-street bicycle lanes, bus/LRT routes and stops/stations, and street network characteristics on travel time reliability were comprehensively considered from a multimodal perspective. Likewise, a 2.5-mile-long section of the Blue Line LRT extension, which connects University City Blvd and Mallard Creek Church Rd on N Tryon St in Charlotte, North Carolina, was considered for simulation-based operational analysis. Vissim traffic simulation software was used to compute and compare delay, queue length, and maximum queue length at nine intersections to evaluate the influence of vehicles, LRT, pedestrians, and bicyclists, individually and/or combined. The statistical significance of variations in travel time reliability were particularly less in the case of links on N Tryon St with the Blue Line LRT extension. However, a decrease in travel time reliability on some links was observed on the parallel route (I-85) and cross-streets. While a decrease in vehicle delay on northbound and southbound approaches of N Tryon St was observed in most cases after the LRT is in operation, the cross-streets of N Tryon St incurred a relatively higher increase in delay after the LRT is in operation. The current pedestrian and bicycling activity levels seemed insignificant to have an influence on vehicle delay at intersections. The methodological approaches from this research can be used to assess the performance of a transportation facility and identify remedial solutions from a multimodal perspective.

scholarly journals Overview of road performance on the tsunami evacuation road during the n-COVID19 pandemic

2021 ◽  
Vol 331 ◽  
pp. 06006
Author(s):  
Yossyafra ◽  
Anyta Ramadhani ◽  
Vina Gusman ◽  
Monica Herimarni
Keyword(s):  
Large Scale ◽  
New Normal ◽  
Tsunami Disaster ◽  
Traffic Conditions ◽  
Normal Period ◽  
Road Performance ◽  
And Performance ◽  
Traffic Disturbance ◽  
The City ◽  
Better Than

The COVID-19 pandemic has changed the world in various sectors and human activities. Limiting human activity and mobility also has an impact on transportation and traffic. This study aims to calculate the capacity and performance of roads under normal pandemic conditions before PSBB (Large-Scale Social Restrictions) in April 2020 and New Normal in July 2002, as well as predict traffic conditions if the Tsunami disaster hits the city during both periods. Tsunami Evacuation roads in Padang City were selected for analysis. The Indonesian Road Capacity Manual 1997 on urban roads is used as a reference for analyzing road performance indicators. The results showed that; road performance during the PSBB period was better than the New Normal period. The effect of volume and side traffic disturbance factors in the New Normal period makes a significant decrease in performance. Through prediction simulations, if a Tsunami occurs in the two study periods, the analyzed roads can relatively serve evacuation movements. However, the capacity needs to be increased for normal conditions.

Performance Evaluation of Public IaaS Clouds for Web 2.0 Applications Using CloudStone Benchmark

2018 ◽  
pp. 292-314
Author(s):  
Sanjay P. Ahuja ◽  
Neha Soni
Keyword(s):  
Web 2.0 ◽  
Web Application ◽  
Cloud Service ◽  
Cloud Services ◽  
Public Cloud ◽  
Data Intensive ◽  
Social Events ◽  
Amazon Ec2 ◽  
And Performance ◽  
Workload Generator

Web 2.0 applications have become ubiquitous over the past few years because they provide useful features such as a rich, responsive graphical user interface that supports interactive and dynamic content. Social networking websites, blogs, auctions, online banking, online shopping and video sharing websites are noteworthy examples of Web 2.0 applications. The market for public cloud service providers is growing rapidly, and cloud providers offer an ever-growing list of services. As a result, developers and researchers find it challenging when deciding which public cloud service to use for deploying, experimenting or testing Web 2.0 applications. This study compares the scalability and performance of a social-events calendar application on two Infrastructure as a Service (IaaS) cloud services – Amazon EC2 and HP Cloud. This study captures and compares metrics on three different instance configurations for each cloud service such as the number of concurrent users (load), as well as response time and throughput (performance). Additionally, the total price of the three different instance configurations for each cloud service is calculated and compared. This comparison of the scalability, performance and price metrics provides developers and researchers with an insight into the scalability and performance characteristics of the three instance configurations for each cloud service, which simplifies the process of determining which cloud service and instance configuration to use for deploying their Web 2.0 applications. This study uses CloudStone – an open-source, three-tier web application benchmarking tool that simulates Web 2.0 application activities – as a realistic workload generator and to capture the intended metrics. The comparison of the collected metrics indicates that all of the tested Amazon EC2 instance configurations provide better scalability and lower latency at a lower cost than the respective HP Cloud instance configurations; however, the tested HP Cloud instance configurations provide a greater storage capacity than the Amazon EC2 instance configurations, which is an important consideration for data-intensive Web 2.0 applications.

scholarly journals Travel Time Differences between Cargo Cycles and Cars in Commercial Transport Operations

2019 ◽  
Vol 2673 (8) ◽  
pp. 623-637 ◽  
Author(s):  
Johannes Gruber ◽  
Santhanakrishnan Narayanan
Keyword(s):  
Travel Time ◽  
Real Life ◽  
Time Difference ◽  
Significant Variable ◽  
Factors Affecting ◽  
Traffic Conditions ◽  
Time Performance ◽  
Trip Distance ◽  
Business Sectors ◽  
Lack Of Knowledge

Cargo cycles are gaining more interest among commercial users from different business sectors, and they compete with cars in urban commercial transport. Though many studies show the potential of cargo cycles, there is still a reluctance to deploy them. One possible reason for this is the lack of knowledge regarding their suitability in relation to travel time. Therefore, this study aims to explore cargo cycles’ travel time performance by quantifying the travel time differences between them and conventional vehicles for commercial trips. The authors compare real-life trip data from cargo cycles with Google’s routed data for cars. By doing this, the authors explore the factors affecting the travel time difference and propose a model to estimate this difference. The attributes for the model were selected keeping in mind the ease of obtaining values for the variables. Results indicate cycling trip distance to be the most significant variable. The study shows that expected travel time difference for trips with distances between 0 and 20 km (12.4 mi) ranges from -5 min (cargo cycle 5 min faster) to 40 min with a median of 6 min. This value can decrease if users take the optimal cycling route and the traffic conditions are worse for cars. Although what is an acceptable amount of travel time difference depends on the user, practitioners can be certain of the travel time difference they can expect, which enables them to assess the suitability of cargo cycles for their commercial operations.

A New Continuous Flow Intersection for Urban Road: Architecture, Design, and Simulation

2012 ◽  
Vol 209-211 ◽  
pp. 677-682 ◽  
Author(s):  
Qiu Chen Liu ◽  
Lun Zhang ◽  
Wen Chen Yang
Keyword(s):  
Traffic Control ◽  
Continuous Flow ◽  
Left Turn ◽  
Urban Road ◽  
Traffic Efficiency ◽  
Traffic Conditions ◽  
Simulation Results ◽  
Low Efficiency ◽  
And Performance ◽  
Traffic Organization

In the light that heavy left-turn vehicles and oncoming vehicles conflict at conventional intersection(CI), leading to discontinuity and low efficiency of traffic flow, this paper presents a new continuous flow intersection(CFI) for urban roads. The geometry physical model and design principles of the CFI are illustrated and the CFI is designed from following three aspects: traffic space, traffic organization and traffic control. Experiments taking the CI and corresponding the CFI as the reseach objects are carried on, and performance of the proposed the CFI is validated via VISSIM. Extensive simulation results under five traffic conditions have demonstrated the potential of the proposed the CFI for improvement of traffic efficiency, and the applicability of the CFI in China is discussed considering the characteristics of domestic urban intersections and it indicates that the CFI could be applied to domestic suburb roads.

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