Multi-agent Method Research Articles

Study on the Energy Management System of Electric Vehicle Charging Station Based on Multi-Agent System

Under the constraints of distribution transformer capacity and customer charging needs, a UML model for EMS of EV Charging Station is proposed to analyze energy dispatching functions and integrate control strategies of Charging Station. Due to the fact that EV charging system is a complex adaptive system, Multi-Agent System method is utilized in this model. The UML development process provides an extensible and integrated framework, which lays the foundations for the further development on EMS of EV Charging station.

Solving multi-objective job shop problem using nature-based algorithms: new Pareto approximation features

In this paper the job shop scheduling problem (JSP) with minimizing two criteria simultaneously is considered. JSP is frequently used model in real world applications of combinatorial optimization. Multi-objective job shop problems (MOJSP) were rarely studied. We implement and compare two multi-agent nature-based methods, namely ant colony optimization (ACO) and genetic algorithm (GA) for MOJSP. Both of those methods employ certain technique, taken from the multi-criteria decision analysis in order to establish ranking of solutions. ACO and GA differ in a method of keeping information about previously found solutions and their quality, which affects the course of the search. In result, new features of Pareto approximations provided by said algorithms are observed: aside from the slight superiority of the ACO method the Pareto frontier approximations provided by both methods are disjoint sets. Thus, both methods can be used to search mutually exclusive areas of the Pareto frontier.

Multi-Agent Behavioral Control System for the Ore Grinding Process

In this paper, a small multi-agent system (MAS) is proposed based on behavioral approach for the complex grinding processes. Causal association agents were established according to the material balance of grinding processes, and prediction agents and stability control agents were built by adding prediction and control algorithms. The simulation results prove that the system has good stability and anti-interference performance. Multi-agent behavioral control method can be considered as a potential solution to stabilize grinding processes.

Decentralized manufacturing management by a multi-agent optimal control method

A supply chain management system is defined as communications among suppliers, plants, distribution centres, retailers and demand stimulus. These systems are large scale and multi-agent, and therefore a decentralized control method must be used. Also, demand forecasting, as a challenge in production management, can be estimated by advanced methods or modelled using demand forecasting functions. In this paper, a new decentralized receding horizon control method is used to achieve customer contentment and low-cost inventory in a complete chain of supply, manufacture, assembly, warehouse, distribution and retail units. The main novelty of the method returns to the use of both the move suppression term and the look-ahead idea to increase robustness and smoothness in a supply chain containing assembly units. Also, a Kalman filter estimator is applied to estimate states and output variables. For this purpose, a suitable model and appropriate optimal control method are developed. Finally, the efficiency is indicated regarding simulation results.

Empirical Study on Spatiotemporal Evolution of Terrorism Organization Network

To understand spatiotemporal evolution of terrorism organization network and reveal its information mechanism. In this paper, from the view of network science, statistical physics and multi-agent method are proposed to explore time-space evolution of terrorism organization network. The model of time-space evolution is presented to understand terrorism organization network. In the evolution process, dynamical (correction) changes of nodes and edges with time and space for terrorism organization network are considered by designing algorithm. It is found in numerical simulation that, the evolution of terrorism organization network possess small-world effect and scale-free property at the same time, and the whole network have hierarchical structure with different level centre nodes. Increasing factors of belief and resource can also effect on continuous evolution of network. If government around the world take effectively selected measures to attack the terrorism organization, which can be inhibited to a certain extent or under control. But the counter terrorism is the future still a long-term arduous.

Alliance between agents and optimization in warehouse logistics

Nowadays, logistics has become an important part in the supply chain due to the effects of globalization. A warehouse is a large building where goods are stored, and where they may be shipped, catalogued, or received. When considering the level of effort involved in warehouse operations, the greatest expenditure of effort is in the picking process. In warehouse, the major goal is to improve the efficiency, accurancy and safety of warehouse operations. Supply chain managers focus to gain maximum efficiency for minimum cost. Therefore, Warehouse Management Systemd (WMS) first appeared on the market in the 1980s and have been developed to handle warehouse resources and track and monitor warehouse real-time operations. There are many application of Radio Frequency Identification (RFID) that can be found embedded in items especially in supply chain management. Verification is one of the crucial issues of RFID technology. The purpose of this study is to demonstrate the feasibility of a location using the RFID as an active technology in warehouse management field. In this content, our objective is to combine multi-agent systems and optimization algorithms in order to localize the operator by integrating the indoor positioning system and then optimize operator roote during the picking mission. In this paper, we present an Optimizer Based Agent Communication of Operator Work plan in Warehouse (OBACO2W). Order pickers, using the pick by voice technique, receive and execute the orders sent by the WMS. The purpose of logistics is to establish efficient and satisfy customers requirement. So, we aim to enhance workers productivity by assigning to the order pickers the shortest path for the picking mission. We must first locate the picker adopting the RFID technology. Multi-agent modeling problem can be divided into skills and knowledge to autonomous entities called agents, to provide links and dialogue between these entities by means of communication and interaction. In a multi-agent system, the change of status of certain objects in the environment of change agents can affect their behavior and decisions. Thus, to optimize their choices and to guide their taken decisions, these agents can be equipped with optimization approaches suited to their skills and knowledge. Hence the alliance between the multi-agent systems and optimization methods; these two approaches are perfectly complementary.

Мультиагентные методы и инструментальные средства управления в сервис - ориентированной распределенной вычислительной среде

The paper discusses the issues related to ensuring the effective scaling of the job flow generated by problem-oriented distributed computing systems in heterogeneous Grid with hybrid nodes. Considers the multiagent methods and tools of the new generation, to ensure effective management of the combined job flow of scalable service-oriented software systems and load balancing for computing resources of runtime environment. Describes a high-level tools for developing services of scalable software systems. A distinctive feature of the presented methods and tools is use of elements of the economic theory (such as elements of regulation of supply and demand of resources) in the coordinated multiagent management of cluster Grid with hybrid nodes, both at the Grid level, and at the application level. The functions of problem-oriented computing environment (user application) is realized in the form of Grid-services using technology Web Services Resource Framework and patterns of interaction with local resource managers of Grid nodes. To create the agent of application is used development environment High-performance computing Service-oriented Multiagent System Framework, developed by the authors. A number of scientific services for experimental Grid are given as examples of organization of the problem-oriented computing environment (user application) using methods and tools considered in this paper. The results of their effective functioning is analyzed.

Nature-Inspired Meta-Heuristics on Modern GPUs: State of the Art and Brief Survey of Selected Algorithms

Graphic processing units (GPUs) emerged recently as an exciting new hardware environment for a truly parallel implementation and execution of Nature and Bio-inspired Algorithms with excellent price-to-power ratio. In contrast to common multicore CPUs that contain up to tens of independent cores, the GPUs represent a massively parallel single-instruction multiple-data devices that can nowadays reach peak performance of hundreds and thousands of giga floating-point operations per second. Nature and Bio-inspired Algorithms implement parallel optimization strategies in which a single candidate solution, a group of candidate solutions (population), or multiple populations seek for optimal solution or set of solutions of given problem. Genetic algorithms (GA) constitute a family of traditional and very well-known nature-inspired populational meta-heuristic algorithms that have proved its usefulness on a plethora of tasks through the years. Differential evolution (DE) is another efficient populational meta-heuristic algorithm for real-parameter optimization. Particle swarm optimization (PSO) can be seen as nature-inspired multiagent method in which the interaction of simple independent agents yields intelligent collective behavior. Simulated annealing (SA) is global optimization algorithm which combines statistical mechanics and combinatorial optimization with inspiration in metallurgy. This survey provides a brief overview of the latest state-of-the-art research on the design, implementation, and applications of parallel GA, DE, PSO, and SA-based methods on the GPUs.

Research on Modeling and Simulation of Complex Adaptive Systems Based on Multi-Agent

With the rapid development of complex adaptive systems, traditional modeling and simulation methods have been unable to meet the need of accurate modeling of complex adaptive systems. Therefore, we need a way to accurately describe the characteristics of complex adaptive systems modeling and simulation. Multi-Agent modeling and simulation methods focus on the study of the interaction between multiple subjects. It is an effective way to study complex adaptive system. This paper analyzes the multi-agent modeling process, sets up a rumor spreading model of a small social network through multi-agent modeling and simulation methods,. The simulation results verify the correctness and accuracy of the model.

A Low Power Trust Routing Scheme for Energy Sensitive Wireless Ad Hoc Network

With the rapid development of mobile ad hoc network, energy and trust are important to the network. Energy consumption and trust routing scheme are the main issues in mobile ad hoc network. Trust routing is related to many factors such as hop numbernode residual energy and node behavior. To use the multi-source information, multi-agent information fusion method is used to design trust routing scheme. The definition of trust routing is proposed. Ad hoc On-Demand Distance Vector (AODV) routing protocol is used to validate trust routing scheme, Route Reply (RREP) Message is extended to record node residual energy and behavior information. NS-2 simulator is used to simulate different network scenarios. Simulation results show that low power trust routing scheme can improve the security and efficiency of network, the scheme is sensitive to node residual energy, so it extends the service lifetime of the network.

Research on Diffusion of Warning Based on Multi-Agent Modeling

Quick and highly efficient warning is critical in any emergency evacuation. From the issuing of warning until action taken by people in response, the entire course is a very complex process which is restrained by social, economic, population and other factors. To study the diffusion characteristics of warning in the social network environment as well as the relevant influencing factors, under the guidance of complex system theory and multi-agent modeling method, this paper analyzes the six stages in the diffusion process of warning and builds a diffusion model of warning on the multi-agent software platform Repast based on WS small world network model. Through the study of the simulation results, we find that the diffusion of warning is similar to the diffusion of other information, which showed a similar S-curve.

Research on Grinding Control System Design Method Based on Multi-Agent System Model

This paper proposes a Multi-Agent grinding control system model based on the blackboard model and in accordance with the Multi-Agent Systems modeling method . We hierarchical decompose of the grinding control task, establish a grinding control subsystem model, we establish the specific function of each subsystem model and establish a complete multi-Agent grinding control system structure. We establish a Multi-Agent System based on the blackboard model and multi-Agent Communication and Coordination Mechanism. This paper describes the architecture of the control multi-Agent grinding system and its function results in details and designs a blackboard coordination model, the results shared collaborative mechanisms and Multi-Agent collaboration conflict resolution strategies. This system model reduces the difficulty of the operation of the grinding control, multi-Agent collaboration enhance the system's ability to execute, decision-making consultation mechanisms improves the control precision and accuracy of the system.

Research on Multi-Agent Task Allocation Methods Based on Game Theory

For the complex tasks with time constraints, which can dynamically be added to environment, a task allocation model based on game theory has been established, which has at least a pure Nash equilibrium. A task allocation method has been proposed, which makes agent be able to choose its behavior according to the local information and ensure that agent learns a strict pure strategy Nash Equilibrium quickly by using fictitious play learning method on behavior coordination. Simulation results show that this method is as effective as Chapman and Lius' methods.

Agent Control for Reconfigurable Open Kinematic Chain Manipulators

This paper presents a method for the autonomous control of differently structured open kinematic chains based on multi-agent system technology. The appropriate level of distributing local autonomy (agents) to a manipulative structure is defined, which makes it possible to dynamically change the number, type and structure of manipulative components without modifying their behavioural logic. To achieve fast reconfigurable and scalable manipulative systems, a new multi-agent method is developed for controlling the manipulator kinematics. The new method enables independent manipulator structure from the control system because of its structural and system modularity. The proposed method consists of kinematic equations for use in an agent environment, agent motion-planning algorithms, evaluation functions, agent control logic and kinematic algorithms. The results of simulations and real-world experiments demonstrate the usefulness of the approach for different non-redundant and redundant manipulation structures.

Modeling of Distribution Service Network System in Comprehensive Passenger Transportation Hub

Distribution service network system (DSNS) has dynamic, open, pop and other nonlinear characteristics in terms of structure, environment, and behavior as a subsystem of comprehensive passenger transportation hub system (CPTH). It is a typical complex system. The author putted forward the adaptability of DSNS based on the analysis of complexity of DSNS and analyzed the driving force of adaptability. The model of individual agent and self-adaptive control model of DSNS were designed to provide a dynamic method for adjusting control strategy based on multi-Agent method and CAS theory.

A new meta-heuristic method: Ray Optimization

In this paper a new meta-heuristic method, so-called Ray Optimization, is developed. Similar to other multi-agent methods, Ray Optimization has a number of particles consisting of the variables of the problem. These agents are considered as rays of light. Based on the Snell’s light refraction law when light travels from a lighter medium to a darker medium, it refracts and its direction changes. This behavior helps the agents to explore the search space in early stages of the optimization process and to make them converge in the final stages. This law is the main tool of the Ray Optimization algorithm.

A Multi-agent Based Approach to Reliability Prediction of Train��s Control and Monitoring Software System

This paper describes a reliability prediction approach to the train’s control and monitoring system based on the multi-agent model and simulation. For the train’s control and monitoring system’s large-scale elements, multiple internal interactions and the complexity of the relationship, the multi-agent based reliability prediction method is proposed to meet its features. Firstly, the multi-agent system modeling and simulation method is introduced. Secondly, we focus on the study of the multi-agent based software system reliability modeling and simulation. Finally, in order to verify the validity of this proposed method, an actual project is taken to predict its reliability, and the simulation data is processed and analyzed, and the problem of the complex software system’s reliability prediction is solved.

Agent technologies for feature selection

The feature selection problem is considered. A feature selection method is developed on the basis of the multiagent approach with indirect communications between agents. Software is created to implement the multiagent method. The problem of feature selection for diagnosing chronic bronchitis is solved.

Mobile Multi-Agent Evaluation Method for Wireless Sensor Networks-Based Large-Scale Structural Health Monitoring

Wireless sensor networks are increasingly adopted both in aircraft and civil structural health monitoring. However, due to the limited resources on a wireless sensor node, structural evaluation ability of the wireless sensor network is also limited, especially for large-scale structures. This paper presents a multi-agent cooperation system based on mobile agent technology for wireless sensor network-based structural health monitoring which deals with the evaluation of large-scale structure. Mobile agent with the signal processing or evaluation algorithm is designed to migrate among different sensor nodes and perform network self-organization, data processing, information fusion, and damage estimation. This method can reduce the request to the sensor nodes and achieve a better monitoring and evaluation performance through multiagent cooperation. The proposed mobile multiagent system is evaluated by a large dimension aerospace aluminum structure monitoring experiment in which strain distribution and joint failure are monitored by different sensors. Experimental results show that the system can significantly improve the monitoring performance for large-scale structures.

Nonlinear multi-agent path search method based on OFDM communication

Nonlinear multi-agent path search method based on OFDM communication