Development of Multi Agent Resource Conversion Processes Model and Simulation System

The mathematical model of multi agent resource conversion processes (RCP) is developed by the means of discrete-event simulation systems and expert systems. Within the framework of mathematical model RCP are defined: production system of the RCP structure, that taking into account conflicts origin. The discrete-event simulation system "BPsim" is developed on the basis of the multi agent RCP mathematical model. The "BPsim" system is inculcated on the firms in Ural region (Russia). © Springer-Verlag Berlin Heidelberg 2006

Application of Supercomputer Technologies for Simulation of Socio-Economic Systems

To date, an extensive experience has been accumulated in investigation of problems related to quality, assessment of management systems, modeling of economic system sustainability. The studies performed have created a basis for formation of a new research area — Economics of Quality. Its tools allow to use opportunities of model simulation for construction of the mathematical models adequately reflecting the role of quality in natural, technical, social regularities of functioning of the complex socioeconomic systems. Extensive application and development of models, and also system modeling with use of supercomputer technologies, on our deep belief, will bring the conducted researches of social and economic systems to essentially new level. Moreover, the current scientific research makes a significant contribution to model simulation of multi-agent social systems and that isn’t less important, it belongs to the priority areas in development of science and technology in our country. This article is devoted to the questions of supercomputer technologies application in public sciences, first of all, — regarding technical realization of the large-scale agent-focused models (AFM). The essence of this tool is that owing to increase in power of computers it became possible to describe the behavior of many separate fragments of a difficult system, as social and economic systems represent. The article also deals with the experience of foreign scientists and practicians in launching the AFM on supercomputers, and also the example of AFM developed in CEMI RAS, stages and methods of effective calculating kernel display of multi-agent system on architecture of a modern supercomputer will be analyzed. The experiments on the basis of model simulation on forecasting the population of St. Petersburg according to three scenarios as one of the major factors influencing the development of social and economic system and quality of life of the population are presented in the conclusion

A modular hybrid simulation framework for complex manufacturing system design

For complex manufacturing systems, the current hybrid Agent-Based Modelling and Discrete Event Simulation (ABM–DES) frameworks are limited to component and system levels of representation and present a degree of static complexity to study optimal resource planning. To address these limitations, a modular hybrid simulation framework for complex manufacturing system design is presented. A manufacturing system with highly regulated and manual handling processes, composed of multiple repeating modules, is considered. In this framework, the concept of modular hybrid ABM–DES technique is introduced to demonstrate a novel simulation method using a dynamic system of parallel multi-agent discrete events. In this context, to create a modular model, the stochastic finite dynamical system is extended to allow the description of discrete event states inside the agent for manufacturing repeating modules (meso level). Moreover, dynamic complexity regarding uncertain processing time and resources is considered. This framework guides the user step-by-step through the system design and modular hybrid model. A real case study in the cell and gene therapy industry is conducted to test the validity of the framework. The simulation results are compared against the data from the studied case; excellent agreement with 1.038% error margin is found in terms of the company performance. The optimal resource planning and the uncertainty of the processing time for manufacturing phases (exo level), in the presence of dynamic complexity is calculated

An overview of the VRS virtual platform

This paper provides an overview of the development of the virtual platform within the European Commission funded VRShips-ROPAX (VRS) project. This project is a major collaboration of approximately 40 industrial, regulatory, consultancy and academic partners with the objective of producing two novel platforms. A physical platform will be designed and produced representing a scale model of a novel ROPAX vessel with the following criteria: 2000 passengers; 400 cabins; 2000 nautical mile range, and a service speed of 38 knots. The aim of the virtual platform is to demonstrate that vessels may be designed to meet these criteria, which was not previously possible using individual tools and conventional design approaches. To achieve this objective requires the integration of design and simulation tools representing concept, embodiment, detail, production, and operation life-phases into the virtual platform, to enable distributed design activity to be undertaken. The main objectives for the development of the virtual platform are described, followed by the discussion of the techniques chosen to address the objectives, and finally a description of a use-case for the platform. Whilst the focus of the VRS virtual platform was to facilitate the design of ROPAX vessels, the components within the platform are entirely generic and may be applied to the distributed design of any type of vessel, or other complex made-to-order products

Incorporating Spatial Complexity into Economic Models of Land Markets and Land Use Change

Recent work in regional science, geography, and urban economics has advanced spatial modeling of land markets and land use by incorporating greater spatial complexity, including multiple sources of spatial heterogeneity, multiple spatial scales, and spatial dynamics. Doing so has required a move away from relying solely on analytical models to partial or full reliance on computational methods that can account for these added features of spatial complexity. In the first part of the paper, we review economic models of urban land development that have incorporated greater spatial complexity, focusing on spatial simulation models with spatial endogenous feedbacks and multiple sources of spatial heterogeneity. The second part of the paper presents a spatial simulation model of exurban land development using an auction model to represent household bidding that extends the traditional Capozza and Helsley (1990) model of urban growth to account for spatial dynamics in the form of local land use spillovers and spatially heterogeneous land characteristics.urban growth, urbanization, land development, spatial dynamics, heterogeneity, agent-based models, spatial interactions, Land Economics/Use, Research Methods/ Statistical Methods,

Agents in Bioinformatics

The scope of the Technical Forum Group (TFG) on Agents in Bioinformatics (BIOAGENTS) was to inspire collaboration between the agent and bioinformatics communities with the aim of creating an opportunity to propose a different (agent-based) approach to the development of computational frameworks both for data analysis in bioinformatics and for system modelling in computational biology. During the day, the participants examined the future of research on agents in bioinformatics primarily through 12 invited talks selected to cover the most relevant topics. From the discussions, it became clear that there are many perspectives to the field, ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages for use by information agents, and to the use of Grid agents, each of which requires further exploration. The interactions between participants encouraged the development of applications that describe a way of creating agent-based simulation models of biological systems, starting from an hypothesis and inferring new knowledge (or relations) by mining and analysing the huge amount of public biological data. In this report we summarise and reflect on the presentations and discussions