scholarly journals Relief Aircraft Dispatch Strategies Based on Different Levels of Information Sharing Systems

Aerospace ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 306
Author(s):  
Qingqi Wang ◽  
Terumitsu Hirata
Keyword(s):  
Dynamic System ◽  
Information Sharing ◽  
Simulation Modeling ◽  
Disaster Relief ◽  
Primary Factor ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Simulation Results ◽  
Aircraft Pilots ◽  
Different Levels

In the wake of a disaster, relief activities are expected to start immediately. To determine a better approach in dispatchment and transportation during relief activities, the primary factor is the communication and information sharing between the various parties such as airports, relief shelters and aircraft pilots. However, the effect of the information-sharing systems on the efficiency of transportation is yet to be clarified, and the differences between transport methods under different information-sharing systems are not yet known. Therefore, in this paper, we proposed different dispatch strategies corresponding to different information sharing levels and utilized the agent-based simulation modeling dynamic system to compare the air relief efficiency of different dispatch strategies. The simulation results demonstrate that the efficiency of relief activities increases as the level of information sharing improves, and different dispatch strategies have an impact on the effect of relief activities.

scholarly journals Learning and Adaptation in Dynamic Transit Assignment Models for Congested Networks

2020 ◽  
Vol 2674 (1) ◽  
pp. 113-124 ◽  
Author(s):  
Oded Cats ◽  
Jens West
Keyword(s):  
Information Provision ◽  
Agent Based Simulation ◽  
Transit Assignment ◽  
Agent Based ◽  
Transit Network ◽  
Passenger Demand ◽  
Congested Networks ◽  
Learning And Adaptation ◽  
Assignment Models ◽  
Different Levels

The distribution of passenger demand over the transit network is forecasted using transit assignment models which conventionally assume that passenger loads satisfy network equilibrium conditions. The approach taken in this study is to model transit path choice as a within-day dynamic process influenced by network state variation and real-time information. The iterative network loading process leading to steady-state conditions is performed by means of day-to-day learning implemented in an agent-based simulation model. We explicitly account for adaptation and learning in relation to service uncertainty, on-board crowding and information provision in the context of congested transit networks. This study thus combines the underlying assignment principles that govern transit assignment models and the disaggregate demand modeling enabled by agent-based simulation modeling. The model is applied to a toy network for illustration purposes, followed by a demonstration for the rapid transit network of Stockholm, Sweden. A full-scale application of the proposed model shows the day-to-day travel time and crowding development for different levels of network saturation and when deploying different levels of information availability.

Business Applications of Social Agent-Based Simulation

2000 ◽  
Vol 03 (01n04) ◽  
pp. 451-461 ◽  
Author(s):  
Eric Bonabeau
Keyword(s):  
Stock Market ◽  
Real World ◽  
Simulation Modeling ◽  
Theme Park ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Social Agent ◽  
Business Applications ◽  
Market Simulation

Agent-based simulation is a powerful simulation modeling technique that has seen a number of applications in the last five years, including applications to real-world business problems. In this chapter I introduce agent-based simulation and review three applications to business problems: a theme park simulation, a stock market simulation, and a bankwide simulation.

Evolutionary Game Model of Information Sharing Behavior in Supply Chain Network With Agent-Based Simulation

2019 ◽  
Vol 15 (2) ◽  
pp. 54-68 ◽  
Author(s):  
Jian Tan ◽  
Guoqiang Jiang ◽  
Zuogong Wang
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Evolutionary Game ◽  
Supply Chain Network ◽  
Agent Based Simulation ◽  
Control Cost ◽  
Agent Based ◽  
Supply Chain Networks ◽  
Network Information ◽  
Sharing Behavior

In the supply chain network, information sharing between enterprises can produce synergistic effect and improve the benefits. In this article, evolutionary game theory is used to analyse the evolution process of the information sharing behaviour between supply chain network enterprises with different penalties and information sharing risk costs. Analysis and agent-based simulation results show that when the amount of information between enterprises in supply chain networks is very large, it is difficult to form a sharing of cooperation; increase penalties, control cost sharing risk can increase the probability of supply chain information sharing network and shorten the time for information sharing.

Agent-Based Simulation Modeling in Social and Organizational Domains

SIMULATION ◽  
2005 ◽  
Vol 81 (3) ◽  
pp. 173-174 ◽  
Author(s):  
Bruce Edmonds ◽  
Michael Möhring
Keyword(s):  
Simulation Modeling ◽  
Agent Based Simulation ◽  
Agent Based

scholarly journals Genetic incompatibility combined with female-lethality is effective and robust in simulations of Aedes aegypti population control

2018 ◽  
Author(s):  
Maciej Maselko ◽  
Stephen Heinsch ◽  
Siba Das ◽  
Michael J. Smanski
Keyword(s):  
Aedes Aegypti ◽  
Simulation Modeling ◽  
Population Control ◽  
Genetic Resistance ◽  
Effective Strategy ◽  
Agent Based Simulation ◽  
Genetic Incompatibility ◽  
Agent Based ◽  
Gene Drives ◽  
Aegypti Population

Recent reports of CRISPR/Cas9-based suppression gene drives in insects underscore the challenge of overcoming genetic resistance. Here we present results from agent-based simulation modeling of a novel Field-Amplified Male Sterility System (FAMSS) that outperforms suppression gene drives when challenged with genetic resistance. FAMSS combines a recently described synthetic genetic incompatibility approach with previously demonstrated female-lethality constructs. Our results suggest that FAMSS will be an effective strategy for temporally and spatially self-limited suppression of the disease vectoring mosquito, Aedes aegypti.

The Effects of Different Interaction Protocols in Agent-Based Simulation of Social Activities

2012 ◽  
pp. 11-24
Author(s):  
Nicole Ronald ◽  
Theo Arentze ◽  
Harry Timmermans
Keyword(s):  
Decision Making ◽  
Decision Process ◽  
Social Activity ◽  
Travel Behaviour ◽  
Large Role ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Interaction Protocols ◽  
Modelling Techniques ◽  
Simulation Results

Decision making in models of activity and travel behaviour is usually individual-based and focuses on outcomes rather than the decision process. Using agent-based modelling techniques and incorporating interaction protocols into the model can assist in modelling decision-making in more detail. This paper describes an agent-based model of social activity generation and scheduling, in which utility-based agents interact with each other to schedule activities. Six different protocols are tested. The authors show that the model outcomes reflect minor changes in the protocol, while changing the order of the protocol leads to significantly different outcomes, hence the protocol plays a large role in the simulation results and should be studied in more detail.

Sign in / Sign up

Export Citation Format

Share Document