Agent based approaches for smart charging strategy for electric vehicles

This paper presents an agent process simulation to control and monitor the Electric Vehicle charging process, using existing power distribution limitations and microgeneration capacity. The goal is to simulate the consumers’ energy consumption and their unexpected behavior, using past experience and taking into account distribution network and home power limitation to find an intelligent charging pattern. This paper proposes a novel approach for this problem based on an agent-based simulation platform where stochastic process is adopted to perform unexpected user behavior. This simulation tool can be used to determine the capability of the actual electrical distribution network for supply energy to the final consumers and for charge the bank of batteries of electrical vehicles, which can occur simultaneously.Fundação para a Ciência e a Tecnologia (FCT) - Project MIT-PT/EDAM-SMS/0030/2008.MIT-Portugal Progra

Agent-Based Modeling: The Right Mathematics for the Social Sciences?

This study provides a basic introduction to agent-based modeling (ABM) as a powerful blend of classical and constructive mathematics, with a primary focus on its applicability for social science research.� The typical goals of ABM social science researchers are discussed along with the culture-dish nature of their computer experiments. The applicability of ABM for science more generally is also considered, with special attention to physics. Finally, two distinct types of ABM applications are summarized in order to illustrate concretely the duality of ABM: Real-world systems can not only be simulated with verisimilitude using ABM; they can also be efficiently and robustly designed and constructed on the basis of ABM principles. �

Agent-based model of maritime search operations:a validation using test-driven simulation modeling

Maritime search operations (and search operations in general) are one of the classic applications of Operational Research (OR). This paper presents a generic agent-based model for maritime search operations which can be used to analyse operations such as search and rescue and patrol. Agent-based simulation (ABS) is a relatively new addition to existing OR techniques. The key elements of an ABS model are agents, their behaviours and their interactions with other agents and the environment. A search operation involves at least two types of agent: a searcher and a target. The unique characteristic of ABS is that we model agents’ behaviours and their interactions at the individual level. Hence, ABS offers an alternative modelling approach to analyse search operations. The second objective of our work is to show how test-driven simulation modelling (TDSM) can be used to validate the agent-based maritime search-operation model

Spatial Modeling using Agents

Simulation is a decision support technique that is often used to represent systems of interest and to experiment with them. Multi-Agent Simulation (MAS) is increasingly being used for modeling systems that comprise of autonomous and interacting system components. In such systems, the interactions among the underlying system components may be dependent on their spatial characteristics (e.g., dimension and location in three-dimensional space). The work presented in this paper describes an agent-based approach to spatial modeling through the use of a case study in container loading. The contribution of this paper is the demonstration of the feasibility of using MAS for spatial, proximity-based modeling, wherein not only agent behavior but also their physical dimension and their location in the three dimensional space are key considerations

An Algorithm for Multi-Objective Multi-Agent Optimization

Multi-agent optimization problems with many objective functions have drawn much interest over the past two decades. Many works on the subject minimize the sum of objective functions, which implicitly carries a decision about the problem formulation. Indeed, it represents a special case of a multi-objective problem, in which all objectives are prioritized equally. To the best of our knowledge, multi-objective optimization applied to multi-agent systems remains largely unexplored. Therefore, we propose a distributed algorithm that allows the exploration of Pareto optimal solutions for the non-homogeneously weighted sum of objective functions. In the problems we consider, each agent has one objective function to minimize based on a gradient method. Agents update their decision variables by exchanging information with other agents in the network. Information exchanges are weighted by each agent's individual weights that encode the extent to which they prioritize other agents' objectives. This paper provides a proof of convergence, performance bounds, and explicit limits for the results of agents' computations. Simulation results with different sizes of networks demonstrate the efficiency of the proposed approach and how the choice of weights impacts the agents' final result

Съвременно приложение на многоагентните симулационни модели в изследванията и в практиката

В публикацията са представени някои от съвременните резултати в областта на изграждането на многоагентни симулационни модели и полезното им приложение в редица изследователски и практически дейности. Разгледани са отличителните характеристики на многоагентните системи, мотивите за разработването им като инструментални средства, структурата им и основните изграждащи ги компоненти. Отбелязани са основните методологически проблеми на създаването на многоагентни системи за симулационно моделиране. Посочени са някои типични предметни области за приложение на многоагентните симулационни модели. Включено е описание и сравнителен анализ на някои от най-популярните софтуерни инструменти за многоагентно симулиране

Analysing trade-offs in container loading: Combining load plan construction heuristics with agent-based simulation

This is the accepted version of the following article: Analysing Trade-offs in Container Loading: Combining Load Plan Construction Heuristics with Agent-based Simulation. International Transactions in Operational Research, 20(4): 471-491which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/itor.12017/abstractIn this paper we describe two operations research techniques, cutting and packing optimisation (CPO) and simulation, and present a multi-methodology approach for analysing the trade-offs between loading efficiency and various important practical considerations in relation to the cargo, such as its stability, fragility or possible cross-contamination between different types of items over time. The feasibility of this approach is demonstrated by considering a situation where the items to be loaded have differing degrees of perishability and where badly deteriorated items can affect those in their immediate vicinity (e.g. through the spread of mould). Our approach uses the output of the CPO algorithms to create agents that simulate the spread of mould through proximity-based interactions between the agents. The results show the trade-offs involved in container utilisation and the propagation of mould, without evidence of any correlation between them. The contribution of this research is the methodology and the feasibility study

Assessing historical realibility of the agent-based model of the global energy system

This study looks at the historical reliability of the agent-based model of the global energy system. We present a mathematical framework for the agent-based model calibration and sensitivity analysis based on historical observations. Simulation consistency with the historical record is measured as a distance between two vectors of data points and inference on parameter values is done from the probability distribution of this stochastic estimate. Proposed methodology is applied to the model of the global energy system. Some model properties and limitations followed from calibration results are discussed

Exploring the role of large-scale immersive computing environments in collaboration between engineering and design students

In order to solve the engineering challenges of today, multidisciplinary collaboration is essential. Unfortunately there are many obstacles to communication between disciplines, such as incongruent vocabularies and mismatched knowledge bases, which can make collaboration difficult. The silos separating disciplines, created through focused educational curriculum, are also a large barrier. During their education, designers and engineers are encouraged to employ specific methods unique to their discipline to share ideas with their peers. In many cases, however, these methods do not translate between disciplines, making it challenging for two groups to exchange ideas and perspectives effectively. There are, however, some tools that have emerged to help bridge the gap between designers and engineers. Currently, the most pervasive solution to these challenges is Computer-Aided Drafting (CAD) software. This software is used by both engineers and designers, allowing both groups to design and evaluate models in a common medium. This makes it decidedly easier for these two groups to collaborate with each other. However, CAD has its own limitations. Navigating in a three-dimensional environment with two dimensional input devices is unnatural and imposes an additional physical and cognitive load on the user. Desktop screens also limit decision-making capabilities due to their small size and the potential to create distorted impressions of size and scale of models larger than the computer screen. Large-Scale Immersive Computing Environments (LSICEs) improve upon the benefits of CAD software. They provide users with the ability to not only visualize their designs three dimensionally, but also allow for natural interactions with 3D models and the ability to view a design as the designer had intended, in true scale. This can improve the ability of users to collaborate in a number of different ways. The natural interaction interface allows students to focus on sharing ideas with their collaborators. Additionally, the common medium makes it much easier for the two groups to communicate with each other, eliminating one of the main obstacles to interdisciplinary collaboration in education. This research seeks to gain a better understanding of how design and engineering design students use LSICEs to collaborate with peers, both within and outside of their discipline. Two studies were conducted. In the first study, two different classes of students used a LSICE as a tool during their design process. The first class was a design class that utilized the LSICE as a part of three design projects throughout the semester. The second class was a sophomore engineering design class. These students also used the LSICE as a part of their design process, however these students used the virtual environment over the course of a single semester-long design project. Students were given a short survey at the end of their experiences in the virtual environment. From this study, some interesting results emerged. Both groups of students indicated that the virtual environment was a benefit to their design process, regardless of background or time spent in the space. Statistical analysis of the students\u27 responses revealed no significant differences between the two groups of students. The final study brought engineering and design students together to complete a design review task within the LSICE. This study was conducted in order to evaluate the role that LSICEs play in facilitating collaboration between engineers and designers. Upon conclusion of the design review, students were given a survey to gather information of their perceptions of the virtual environment in visualizing designs, communicating with their peers and interacting with designs. From this study it became quite clear that students find LSICEs to be effective in facilitating communication between disciplines. Additionally, the majority of students commented on the positive effect that the natural interaction interface had on their ability to evaluate the design. Throughout each of these studies, common themes emerged between both groups. Student responses show many perceived benefits to LSICEs which have the potential to inspire student-driven interdisciplinary collaboration. Participants found that the environment improved their ability to communicate, whether it be with peers within their disciplines or when working in interdisciplinary groups. Students also found that interacting in the environment in a natural way improved their ability to make judgments about spatial relationships among components. The results from this research are quite promising. Providing students with collaboration tools that support natural human interaction with CAD models of real size has the potential for greatly improving a student\u27s educational experience. Manipulating full size CAD models encourages students to visualize the size and shape of the final design before it is built. Seeing the designs in full scale allows everyone on the team to experience the design and provide their input into the design discussions. This research continues an effort in academia to leverage cutting edge technology to improve student learning by providing unique opportunities to interact with peers in design teams, promoting graduates who are well equipped to work effectively across disciplines to address the challenges of today