Implementing an agent-based model with a spatial visual display in discrete-event simulation software

There has been an increasing interest in the use of agent-based simulation and some discussion of the relative merits of this approach as compared to discrete-event simulation. There are differing views on whether an agent-based simulation offers capabilities that discrete-event cannot provide or whether all agent-based applications can at least in theory be undertaken using a discrete-event approach. This paper presents a simple agent-based NetLogo model and corresponding discrete-event versions implemented in the widely used ARENA software. The two versions of the discrete-event model presented use a traditional process flow approach normally adopted in discrete-event simulation software and also an agent-based approach to the model build. In addition a real-time spatial visual display facility is provided using a spreadsheet platform controlled by VBA code embedded within the ARENA model. Initial findings from this investigation are that discrete-event simulation can indeed be used to implement agent-based models and with suitable integration elements such as VBA provide the spatial displays associated with agent-based software.

Human Behavious Modelling for Discrete Event and Agent Based Simulation: A Case Study

This study is about the comparison of simulation techniques between Discrete Event Simulation (DES) and Agent Based Simulation (ABS). DES is one of the best-known types of simulation techniques in Operational Research. Recently, there has been an emergence of another technique, namely ABS. One of the qualities of ABS is that it helps to gain a better understanding of complex systems that involve the interaction of people with their environment as it allows to model concepts like autonomy and pro-activeness which are important attributes to consider. Although there is a lot of literature relating to DES and ABS, we have found none that focuses on exploring the capability of both in tackling the human behaviour issues which relates to queuing time and customer satisfaction in the retail sector. Therefore, the objective of this study is to identify empirically the differences between these simulation techniques by stimulating the potential economic benefits of introducing new policies in a department store. To apply the new strategy, the behaviour of consumers in a retail store will be modelled using the DES and ABS approach and the results will be compared. We aim to understand which simulation technique is better suited to human behaviour modelling by investigating the capability of both techniques in predicting the best solution for an organisation in using management practices. Our main concern is to maximise customer satisfaction, for example by minimising their waiting times for the different services provided.

Modelling and analysing human behaviour in a department store using discrete event and agent based simulation

Discrete Event Simulation (DES) is a very popular simulation technique in Operational Research. Recently, there has been the emergence of another technique, namely Agent Based Simulation (ABS). Although there is a lot of literature relating to DES and ABS, we have found less that focuses on exploring the capabilities of both in tackling human behaviour issues. In order to understand the gap between these two simulation techniques, therefore, our aim is to understand the distinctions between DES and ABS models with the real world phenomenon in modelling and simulating human behaviour. In achieving the aim, we have carried out a case study at a department store. Both DES and ABS models will be compared using the same problem domain which is concerning on management policy in a fitting room. The behaviour of staffs while working and customers’ satisfaction will be modelled for both models behaviour understanding.

An agent-based simulation of in-store customer experiences

Agent-based modelling and simulation offers a new and exciting way of understanding the world of work. In this paper we describe the development of an agent-based simulation model, designed to help to understand the relationship between human resource management practices and retail productivity. We report on the current development of our simulation model which includes new features concerning the evolution of customers over time. To test some of these features we have conducted a series of experiments dealing with customer pool sizes, standard and noise reduction modes, and the spread of the word of mouth. Our multidisciplinary research team draws upon expertise from work psychologists and computer scientists. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents offer potential for fostering sustainable organisational capabilities in the future.

Investigating output accuracy for a discrete event simulation model and an agent based simulation model

In this paper, we investigate output accuracy for a Discrete Event Simulation (DES) model and Agent Based Simulation (ABS) model. The purpose of this investigation is to find out which of these simulation techniques is the best one for modelling human reactive behaviour in the retail sector. In order to study the output accuracy in both models, we have carried out a validation experiment in which we compared the results from our simulation models to the performance of a real system. Our experiment was carried out using a large UK department store as a case study. We had to determine an efficient implementation of management policy in the store’s fitting room using DES and ABS. Overall, we have found that both simulation models were a good representation of the real system when modelling human reactive behaviour.

Concurrent multi-scale modeling of civil infrastructures for analyses on structural deterioration—Part I : Modeling methodology and strategy

This paper aims to develop the methodology and strategy for concurrent finite element modeling of civil infrastructures at the different scale levels for the purposes of analyses of structural deteriorating. The modeling strategy and method were investigated to develop the concurrent multi-scale model of structural behavior (CMSM-of-SB) in which the global structural behavior and nonlinear damage features of local details in a large complicated structure could be concurrently analyzed in order to meet the needs of structural-state evaluation as well as structural deteriorating. In the proposed method, the “large-scale” modeling is adopted for the global structure with linear responses between stress and strain and the “small-scale” modeling is available for nonlinear damage analyses of the local welded details. A longitudinal truss in steel bridge decks was selected as a case to study how a CMSM-of-SB was developed. The reduced-scale specimen of the longitudinal truss was studied in the laboratory to measure its dynamic and static behavior in global truss and local welded details, while the multi-scale models using constraint equations and substructuring were developed for numerical simulation. The comparison of dynamic and static response between the calculated results by different models indicated that the proposed multi-scale model was found to be the most efficient and accurate. The verification of the model with results from the tested truss under the specific loading showed that, responses at the material scale in the vicinity of local details as well as structural global behaviors could be obtained and fit well with the measured results. The proposed concurrent multi-scale modeling strategy and implementation procedures were applied to Runyang cable-stayed bridge (RYCB) and the CMSM-of-SB of the bridge deck system was accordingly constructed as a practical application.

Concurrent multi-scale modeling of civil infrastructures for analyses on structural deteriorating—Part II : Model updating and verification

This paper is a continuation of the paper titled “Concurrent multi-scale modeling of civil infrastructure for analyses on structural deteriorating—Part I: Modeling methodology and strategy” with the emphasis on model updating and verification for the developed concurrent multi-scale model. The sensitivity-based parameter updating method was applied and some important issues such as selection of reference data and model parameters, and model updating procedures on the multi-scale model were investigated based on the sensitivity analysis of the selected model parameters. The experimental modal data as well as static response in terms of component nominal stresses and hot-spot stresses at the concerned locations were used for dynamic response- and static response-oriented model updating, respectively. The updated multi-scale model was further verified to act as the baseline model which is assumed to be finite-element model closest to the real situation of the structure available for the subsequent arbitrary numerical simulation. The comparison of dynamic and static responses between the calculated results by the final model and measured data indicated the updating and verification methods applied in this paper are reliable and accurate for the multi-scale model of frame-like structure. The general procedures of multi-scale model updating and verification were finally proposed for nonlinear physical-based modeling of large civil infrastructure, and it was applied to the model verification of a long-span bridge as an actual engineering practice of the proposed procedures.

A study on matching and multi-objective fuzzy control strategy of heavy truck suspension system

Matching method of heavy truck-rear air suspensions is discussed, and a fuzzy control strategy which improves both ride comfort and road friendliness of truck by adjusting damping coefficients of the suspension system is found. In the first place, a Dongfeng EQ1141G7DJ heavy truck’s ten DOF whole vehicle-road model was set up based on Matlab/Simulink and vehicle dynamics. Then appropriate passive air suspensions were chosen to replace the original rear leaf springs of the truck according to truck-suspension matching criterions, consequently, the stiffness of front leaf springs were adjusted too. Then the semi-active fuzzy controllers were designed for further enhancement of the truck’s ride comfort and the road friendliness. After the application of semi-active fuzzy control strategy through simulation, is was indicated that both ride comfort and road friendliness could be enhanced effectively under various road conditions. The strategy proposed may provide theory basis for design and development of truck suspension system in China.

Self-commutated current source converter with multi-level current reinjection

The multi-level current reinjection concept described in literature is well-known to produce high quality AC current waveforms in high power and high voltage self-commutating current source converters. This paper proposes a novel reinjection circuitry which is capable of producing a 7-level reinjection current. It is shown that this reinjection current effectively increases the pulse number of the converter to 72. The use of PSCAD/EMTDC simulation validates the functionality of the proposed concept illustrating its effectiveness on both AC and DC sides of the converter.

Multi-vehicles interaction graph model for cooperative collision warning system

Cooperative collision warning system for road vehicles, enabled by recent advances in positioning systems and wireless communication technologies, can potentially reduce traffic accident significantly. To improve the system, we propose a graph model to represent interactions between multiple road vehicles in a specific region and at a specific time. Given a list of vehicles in vicinity, we can generate the interaction graph using several rules that consider vehicle's properties such as position, speed, heading, etc. Safety applications can use the model to improve emergency warning accuracy and optimize wireless channel usage. The model allows us to develop some congestion control strategies for an efficient multi-hop broadcast protocol.

Cross voltage control with inner hysteresis current control for multi-output boost converter

Multi-output boost (MOB) converter is a novel DC-DC converter unlike the regular boost converter, has the ability to share its total output voltage and to have different series output voltage from a given duty cycle for low and high power applications. In this paper, discrete voltage control with inner hysteresis current control loop has been proposed to keep the simplicity of the control law for the double-output MOB converter, which can be implemented by a combination of analogue and logical ICs or simple microcontroller to constrain the output voltages of MOB converter at their reference voltages against variation in load or input voltage. The salient features of the proposed control strategy are simplicity of implementation and ease to extend to multiple outputs in the MOB converter. Simulation and experimental results are presented to show the validity of control strategy.

Multi-output DC-DC converters based on diode-clamped converters configuration : topology and control strategy

This paper presents a new DC-DC Multi-Output Boost (MOB) converter which can share its total output between different series of output voltages for low and high power applications. This configuration can be utilised instead of several single output power supplies. This is a compatible topology for a diode-clamed inverter in the grid connection systems, where boosting low rectified output-voltage and series DC link capacitors is required. To verify the proposed topology, steady state and dynamic analysis of a MOB converter are examined. A simple control strategy has been proposed to demonstrate the performance of the proposed topology for a double-output boost converter. The topology and its control strategy can easily be extended to offer multiple outputs. Simulation and experimental results are presented to show the validity of the control strategy for the proposed converter.

Multi-output buck-boost converter with enhanced dynamic response to load and input voltage changes

This paper presents a new multi-output DC/DC converter topology that has step-up and step-down conversion capabilities. In this topology, several output voltages can be generated which can be used in different applications such as multilevel converters with diode-clamped topology or power supplies with several voltage levels. Steady state and dynamic equations of the proposed multi-output converter have been developed, that can be used for steady state and transient analysis. Two control techniques have been proposed for this topology based on constant and dynamic hysteresis band height control to address different applications. Simulations have been performed for different operating modes and load conditions to verify the proposed topology and its control technique. Additionally, a laboratory prototype is designed and implemented to verify the simulation results.

Reading the play : adaptation by prediction of agent motion

An adaptive agent improves its performance by learning from experience. This paper describes an approach to adaptation based on modelling dynamic elements of the environment in order to make predictions of likely future state. This approach is akin to an elite sports player being able to “read the play”, allowing for decisions to be made based on predictions of likely future outcomes. Modelling of the agent‟s likely future state is performed using Markov Chains and a technique called “Motion and Occupancy Grids”. The experiments in this paper compare the performance of the planning system with and without the use of this predictive model. The results of the study demonstrate a surprising decrease in performance when using the predictions of agent occupancy. The results are derived from statistical analysis of the agent‟s performance in a high fidelity simulation of a world leading real robot soccer team.

Probabilistic world modeling for distributed team planning

This paper describes an application of decoupled probabilistic world modeling to achieve team planning. The research is based on the principle that the action selection mechanism of a member in a robot team can select an effective action if a global world model is available to all team members. In the real world, the sensors are imprecise, and are individual to each robot, hence providing each robot a partial and unique view about the environment. We address this problem by creating a probabilistic global view on each agent by combining the perceptual information from each robot. This probabilistic view forms the basis for selecting actions to achieve the team goal in a dynamic environment. Experiments have been carried out to investigate the effectiveness of this principle using custom-built robots for real world performance, in addition, to extensive simulation results. The results show an improvement in team effectiveness when using probabilistic world modeling based on perception sharing for team planning.