scholarly journals An optimized multi agent-based modeling of smart rescue operation

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 93-100 ◽  
Author(s):  
S. Azimi ◽  
M. R. Delavar ◽  
A. Rajabifard
Keyword(s):  
Information Transfer ◽  
Operation Time ◽  
Agent Based Modeling ◽  
Medical Assistance ◽  
Rescue Operation ◽  
Partial Difference ◽  
Agent Based ◽  
Proposed Model ◽  
Emergency Vehicles ◽  
Multi Agent

<p><strong>Abstract.</strong> After the incidence of a disaster, a high demand for first-aid and a huge number of injured will emerge at the affected areas. In this paper, the optimum allocation of the medical assistance to the injured according to a multi-criteria decision making is performed by Multiplicatively Weighted Network Voronoi Diagram (MWNVD). For consideration of the allocation of the injured in the affected area to the appropriate hospitals using the MWNVD and decreasing the gap between the estimated and expected population in the MWNVDs, Particle Swarm Optimization (PSO) is applied to the MWNVDs.<br> This paper proposes a multi agent-based modeling for incorporating the allocation of the medical supplies to the injured according to the generated Voronoi Diagrams of the PSO-MWNVD, wayfinding of emergency vehicles based on the minimum travel distance and time as well as using smart city facilities to expedite the rescue operation. In the proposed model, considering the priority of the injured for receiving the medical assistance, information transfer about the condition of the injured to the hospitals prior to ambulance arrival for providing appropriate treatment, updating of emergency vehicles route based on the blocked streets and etc. are optimized.<br> The partial difference between the estimated and expected population for receiving the medical assistance in MWNVDs is computed as 37&amp;thinsp;%, while the PSO-MWNVD decreased the mentioned difference to 6&amp;thinsp;%. The relief operation time in the proposed model compared to another multi-agent rescue operation model, which uses MWNVD and does not have some facilities of the proposed model, is improved.</p>

scholarly journals Agent Based Load Balancing in Grid Computing

2020 ◽  
Author(s):  
Wided Ali ◽  
Fatima Bouakkaz
Keyword(s):  
Load Balancing ◽  
Heterogeneous Systems ◽  
Agent Based ◽  
Selection Policy ◽  
Development Framework ◽  
Policy Selection ◽  
Proposed Model ◽  
Multi Agent ◽  
Location Policy ◽  
System Characteristics

Load-Balancing is an important problem in distributed heterogeneous systems. In this paper, an Agent-based load-balancing model is developed for implementation in a grid environment. Load balancing is realized via migration of worker agents from overloaded resources to underloaded ones. The proposed model purposes to take benefit of the multi-agent system characteristics to create an autonomous system. The Agent-based load balancing model is implemented using JADE (Java Agent Development Framework) and Alea 2 as a grid simulator. The use of MAS is discussed, concerning the solutions adopted for gathering information policy, location policy, selection policy, worker agents migration, and load balancing.

Adaptive Ensemble Multi-Agent Based Intrusion Detection Model

2010 ◽  
pp. 36-48 ◽  
Author(s):  
Tarek Helmy
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Machine Learning Algorithms ◽  
Agent Based ◽  
Detection Model ◽  
Detection Analysis ◽  
Proposed Model ◽  
Multi Agent

The system that monitors the events occurring in a computer system or a network and analyzes the events for sign of intrusions is known as intrusion detection system. The performance of the intrusion detection system can be improved by combing anomaly and misuse analysis. This chapter proposes an ensemble multi-agent-based intrusion detection model. The proposed model combines anomaly, misuse, and host-based detection analysis. The agents in the proposed model use rules to check for intrusions, and adopt machine learning algorithms to recognize unknown actions, to update or create new rules automatically. Each agent in the proposed model encapsulates a specific classification technique, and gives its belief about any packet event in the network. These agents collaborate to determine the decision about any event, have the ability to generalize, and to detect novel attacks. Empirical results indicate that the proposed model is efficient, and outperforms other intrusion detection models.

The Use of Multi-Agent Systems in Managing Sustainable Supply Chain

2013 ◽  
Vol 315 ◽  
pp. 108-112
Author(s):  
Majid Aarabi ◽  
Muhamad Zameri Mat Saman ◽  
Kuan Yew Wong
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Supply Chains ◽  
Sustainable Supply Chain ◽  
Multi Agent Systems ◽  
Chain Management ◽  
Agent Based ◽  
Goods And Services ◽  
Proposed Model ◽  
Multi Agent

The main purposes and challenges in supply chain management are reducing cost and time. Significantly, factors such as the competition of markets in the globe, limitation of energy, raw and virgin materials, environmental protection crisis and increasing of global population dramatically are causing unprecedented issues for the worldwide supply chains for providing goods and services to customers efficiently and effectively. The sustainability approach for Supply Chain Management (SCM) considers the 6Rs principles in four main stages of the supply chains: Pre-manufacture, Manufacture, Use and Post-use. The use of Multi-Agent System (MAS) prepares the most important requirements of an effective sustainable supply chain. At the same time, this agent-based approach provides reliable and agile systems, which will enable enterprises to accommodate ever changing needs of their customers in the future. In this article, the use of MAS for optimal Sustainable Supply Chain Management (SSCM) is reviewed and the integrated functioning of certain agents resulting in information sharing is also demonstrated. With this idea, an attempt is made to provide a MAS model for the SSCM. In the proposed model, each agent performs a specific function of the organization and shares information with other agents. In order to describe this multi-agent based approach, a simple case study is given to illustrate the sustainable supply chain operations.

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