scholarly journals Disruption Management With Rescheduling of Trips and Vehicle Circulations

2011 ◽  
Author(s):  
Martin Lorek ◽  
Sa´ndor P. Fekete ◽  
Alexander Kro¨ller ◽  
Marc E. Pfetsch
Keyword(s):  
Time Window ◽  
Real Life ◽  
Disruption Management ◽  
Life Test ◽  
Subway System ◽  
Bottle Neck ◽  
Event Based ◽  
Model Features ◽  
Significant Size ◽  
Activity Graph

This paper introduces a combined approach for the recovery of a timetable by rescheduling trips and vehicle circulations for a rail-based transportation system subject to disruptions. We propose a novel event-based integer programming (IP) model. Features include shifting and canceling of trips as well as modifying the vehicle schedules by changing or truncating the circulations. The objective maximizes the number of recovered trips, possibly with delay, while guaranteeing a conflict-free new timetable for the estimated time window of the disruption. We demonstrate the usefulness of our approach through experiments for real-life test instances of relevant size, arising from the subway system of Vienna. We focus on scenarios in which one direction of one track is blocked, and trains have to be scheduled through this bottle-neck. Solving these instances is made possible by contracting parts of the underlying event-activity graph; this allows a significant size reduction of the IP. Usually, the solutions found within one minute are of good quality and can be used as good estimates of recovery plans in an online context.

Exploring Weather Data to Predict Activity Attendance in Event-based Social Network

2021 ◽  
Vol 15 (2) ◽  
pp. 1-25
Author(s):  
Jifeng Zhang ◽  
Wenjun Jiang ◽  
Jinrui Zhang ◽  
Jie Wu ◽  
Guojun Wang
Keyword(s):  
Real Life ◽  
Prediction Performance ◽  
Weather Data ◽  
Gradient Boosting ◽  
User Interest ◽  
Weather Factors ◽  
Event Duration ◽  
Outdoor Activities ◽  
Weather Factor ◽  
Event Based

Event-based social networks (EBSNs) connect online and offline lives. They allow online users with similar interests to get together in real life. Attendance prediction for activities in EBSNs has attracted a lot of attention and several factors have been studied. However, the prediction accuracy is not very good for some special activities, such as outdoor activities. Moreover, a very important factor, the weather, has not been well exploited. In this work, we strive to understand how the weather factor impacts activity attendance, and we explore it to improve attendance prediction from the organizer’s view. First, we classify activities into two categories: the outdoor and the indoor activities. We study the different ways that weather factors may impact these two kinds of activities. We also introduce a new factor of event duration. By integrating the above factors with user interest and user-event distance, we build a model of attendance prediction with the weather named GBT-W , based on the Gradient Boosting Tree. Furthermore, we develop a platform to help event organizers estimate the possible number of activity attendance with different settings (e.g., different weather, location) to effectively plan their events. We conduct extensive experiments, and the results show that our method has a better prediction performance on both the outdoor and the indoor activities, which validates the reasonability of considering weather and duration.

scholarly journals A Generalized Minimum Cost Flow Model for Multiple Emergency Flow Routing

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jianxun Cui ◽  
Shi An ◽  
Meng Zhao
Keyword(s):  
Flow Model ◽  
Time Window ◽  
Programming Model ◽  
Real Life ◽  
Minimum Cost ◽  
Emergency Evacuation ◽  
Mixed Integer ◽  
Fixed Cost ◽  
Minimum Cost Flow ◽  
Cost Flow

During real-life disasters, that is, earthquakes, floods, terrorist attacks, and other unexpected events, emergency evacuation and rescue are two primary operations that can save the lives and property of the affected population. It is unavoidable that evacuation flow and rescue flow will conflict with each other on the same spatial road network and within the same time window. Therefore, we propose a novel generalized minimum cost flow model to optimize the distribution pattern of these two types of flow on the same network by introducing the conflict cost. The travel time on each link is assumed to be subject to a bureau of public road (BPR) function rather than a fixed cost. Additionally, we integrate contraflow operations into this model to redesign the network shared by those two types of flow. A nonconvex mixed-integer nonlinear programming model with bilinear, fractional, and power components is constructed, and GAMS/BARON is used to solve this programming model. A case study is conducted in the downtown area of Harbin city in China to verify the efficiency of proposed model, and several helpful findings and managerial insights are also presented.

scholarly journals Zooming into Real-Life Extraversion – How Personality and Situation Shape Sociability in Social Interactions

2016 ◽  
Author(s):  
Simon Mats Breil ◽  
Katharina Geukes ◽  
Robert Edmund Wilson ◽  
Steffen Nestler ◽  
Simine Vazire ◽  
...  
Keyword(s):  
Social Interactions ◽  
Specific Interaction ◽  
Real Life ◽  
Interaction Effects ◽  
Complex Interplay ◽  
Sampling Studies ◽  
Social Perspectives ◽  
Context Shape ◽  
Event Based ◽  
Main Effects

Here, we provide you with supplemental material (additional tables, data, R-Codes) and a Preprint to the manuscript "Zooming into Real-Life Extraversion - How Personality and Context Shape Sociability in Social Interactions" by Breil et al. (under review). Abstract:What predicts sociable behavior? While main effects of personality and situation characteristics on sociability are well established, the determinants of sociable behavior within real-life social interactions are understudied. Moreover, although such effects are often hypothesized, there is to date little evidence of person-situation interaction effects. Finally, previous research focused on self-reported behavior ratings, and less is known on the partner’s social perspective, i.e. how partners perceive and influence an actor’s behavior. In the current research we investigated predictors of sociable behavior in real-life social interactions across social perspectives, including person and situation main effects as well as person-situation interaction effects. In two experience-sampling studies (Study 1: N = 394, US, time-based; Study 2: N = 124, Germany, event-based), we assessed personality traits with self- and informant reports, self-reported sociable behavior during real-life social interaction, and corresponding information on the situation (dimensional ratings of situation characteristics and categorical situation classifications). In Study 2, we additionally assessed interaction partner-reported behavior. Multilevel analyses provided consistent evidence for main effects of personality and situation features, and for person-situation interaction effects. First, extraverts acted more sociable in general. Second, individuals behaved more sociable in hedonic/positive/low-duty situations (vs. eudaimonic/negative/high-duty situations). Third, the latter was particularly true for extraverts. Further specific interaction effects were found for the other social perspectives. These results are discussed regarding the complex interplay of persons and situations in shaping human behavior.

scholarly journals Zooming into Real-Life Extraversion – how Personality and Situation Shape Sociability in Social Interactions

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Simon M. Breil ◽  
Katharina Geukes ◽  
Robert E. Wilson ◽  
Steffen Nestler ◽  
Simine Vazire ◽  
...  
Keyword(s):  
Social Interactions ◽  
Specific Interaction ◽  
Real Life ◽  
Interaction Effects ◽  
Behavioral Models ◽  
Social Perspective ◽  
Sampling Studies ◽  
Social Perspectives ◽  
Event Based ◽  
Main Effects

What predicts sociable behavior? While main effects of personality and situation characteristics on sociability are well established, there is little evidence for the existence of person-situation interaction effects within real-life social interactions. Moreover, previous research has focused on self-reported behavior ratings, and less is known about the partner’s social perspective, i.e. how partners perceive and influence an actor’s behavior. In the current research, we investigated predictors of sociable behavior in real-life social interactions across social perspectives, including person and situation main effects as well as person-situation interaction effects. In two experience-sampling studies (Study 1: N = 394, US, time-based; Study 2: N = 124, Germany, event-based), we assessed personality traits with self- and informant-reports, self-reported sociable behavior during real-life social interactions, and corresponding information on the situation (categorical situation classifications and dimensional ratings of situation characteristics). In Study 2, we additionally assessed interaction partner-reported actor behavior. Multilevel analyses provided evidence for main effects of personality and situation features, as well as small but consistent evidence for person-situation interaction effects. First, extraverts acted more sociable in general. Second, individuals behaved more sociable in low-effort/positive/low-duty situations (vs. high-effort/negative/high-duty situations). Third, the latter was particularly true for extraverts. Further specific interaction effects were found for the partner’s social perspective. These results are discussed regarding their accordance with different behavioral models (e.g., Trait Activation Theory) and their transferability to other behavioral domains.

An approach towards decentralized control of cooperating non-autonomous multiple robots

Robotica ◽  
2000 ◽  
Vol 18 (5) ◽  
pp. 495-504 ◽  
Author(s):  
Khalid Munawar ◽  
Masayoshi Esashi ◽  
Masaru Uchiyama
Keyword(s):  
Decentralized Control ◽  
Degrees Of Freedom ◽  
Real Life ◽  
Robotic Systems ◽  
Present System ◽  
Multiple Robots ◽  
Experimental Implementation ◽  
Control Scheme ◽  
The Common ◽  
Event Based

This paper introduces an event-based decentralized control scheme for the cooperation between multiple manipulators. This is in contrast to the common practice of using only centralized controls for such cooperation which, consequently, greatly limit the flexibility of robotic systems. The manipulators used in the present system are very simple with only two degrees of freedom, while even one of them is passive. Moreover these manipulators use very few and commonly available sensors only. Computer simulations indicated the applicability of the event-based decentralized control scheme for multi-manipulator cooperation, while real-life experimental implementation has proved that the proposed decentralized control scheme is fairly applicable for very simple and even under-actuated systems too. Hence, this work has opened new doors towards further research in this area. The proposed control scheme is expected to be equally applicable for any mobile or immobile multi-robotic system.

from The Real Life Test

Manoa ◽  
2004 ◽  
Vol 16 (2) ◽  
pp. 67-77
Author(s):  
Bay Anapol
Keyword(s):  
Real Life ◽  
Life Test ◽  
The Real

Dynamic Scheduling Model and Algorithm for Dispatching Trains in High-Speed Railway Passenger Station

2010 ◽  
Author(s):  
Yixiang Yue ◽  
Leishan Zhou
Keyword(s):  
High Speed ◽  
Large Scale ◽  
Job Shop ◽  
Dynamic Scheduling ◽  
Time Window ◽  
Real Life ◽  
Greedy Heuristic ◽  
Railway Station ◽  
High Speed Railway ◽  
Railway Passenger

Regarding the railway station tracks and train running routes as machines, all trains in this railway station as jobs, dispatching trains in high-speed railway passenger stations can be considered as a special type of Job-Shop Problem (JSP). In this paper, we proposed a multi-machines, multi-jobs JSP model with special constraints for Operation Plan Scheduling Problem (OPSP) in high-speed railway passenger stations, and presented a fast heuristic algorithm based on greedy heuristic. This algorithm first divided all operations into several layers according to the yards attributes and the operation’s urgency level. Then every operation was allotted a feasible time window, each operation was assigned to a specified “machine” sequenced or backward sequenced within the time slot, layer by layer according to its priority. As we recorded and modified the time slots dynamically, the searching space was decreased dramatically. And we take the South Beijing High-speed Railway Station as example and give extensive numerical experiment. Computational results based on real-life instance show that the algorithm has significant merits for large scale problems; can both reduce tardiness and shorten cycle times. The empirical evidence also proved that this algorithm is industrial practicable.

Sign in / Sign up

Export Citation Format

Share Document