Showing papers in "International Journal of Simulation and Process Modelling in 2014"

Proposal of a structured methodology for the measure of intangible criteria and for decision making

Abstract: Making decisions requires judgement. Judgement depends on feelings and thoughts and on the ability to interpret the information from the feelings and thoughts which arise from things happening that are inherently tacit, into attributes with different levels of intensity of preference, of importance, or of likelihood. This paper places special emphasis on the measurement of intangible criteria and on their incorporation into the resource allocation process through a proper decision making approach. In this paper, a well-known decision-making method, the analytic hierarchy process (AHP) is applied to identify a quality model to evaluate Italian racecourses’ performances. The aim of the work is to provide a contribution to better understand the decision process of Italian racecourses because it is characterised by a decision process that is not well structured.

Layout and process optimisation: using computer-aided design (CAD) and simulation through an integrated systems design tool

Abstract: The design of production and logistic systems is a process of managing both technical and organisational variants in order to identify the best solution for a given system. This paper discusses design issues of production systems that are applied to an internal logistic system in the automotive industry. As far as the production systems design (PSD) is concerned, three basic classes of software tools usually pertain: computer-aided design (CAD), process simulation, and information systems. However, these software tools have been used with low levels of integration. Vik et al. (2010b, 2010c) proposed integrating these software resources in production systems and developed an advanced tool called integrated design of systems (IDS). The proposed IDS tool involves a wide set of functions for the most common tasks of PSD, from conceptualisation to implementation, including systems analysis (P-Q, cluster, and material flow analysis), automatic generation of simulation models, generation of alternatives for the layout of facilities and factories, material flows display, transportation system design, and iterative buffer size specification. The IDS approach takes advantage of simulation, CAD systems, and their integration. This paper will demonstrate the concept and functionalities of the proposed tool in a real industrial case study.

Analysis and optimisation of inventory management policies for perishable food products: a simulation study

Abstract: In this paper, we analyse three traditional reorder policies, namely economic order interval (EOI), economic order quantity (EOQ) and (S, s), applied to five food products with different shelf-life characteristics; three fresh products with limited shelf-life are considered. An ad hoc simulation model, reproducing a real two-echelon supply chain, was developed under Microsoft ExcelTM to simulate the product flow along the supply chain, according to the three policies. From the simulation, the minimum cost setting is first derived for all policies. Then, additional performance parameters (e.g., the throughput time of items) are computed and compared with the products constraints (e.g., the shelf-life), to assess the real suitability of implementing each policy to the products considered. Because both the supply chain modelled and the products data are derived from a real scenario, our outcomes should be of practical usefulness to inventory managers, to optimise inventory management of perishable products.

Hybrid approach for container terminals performances evaluation and analysis

Abstract: Turnaround time, defined as the total time spent by a vessel within the port area, is one of the most important key performance measures for a container terminal. In this paper, the authors propose a hybrid approach based on simulation and genetic algorithms to investigate vessels’ turnaround time in a real container terminal under different scenarios characterised by increases in containers traffic and vessels traffic. The authors show how a modular simulation model integrated with optimisation algorithms can be used as an advanced support tool to identify resources capacity constraints and to identify how such constraints affect the vessels’ turnaround time.

Testing the behaviour of different inventory control policies in case of extended reverse logistics by using simulation

Abstract: Nowadays, sustainability issues are stressing the importance of the inventory management problem in case of reverse logistics. The aim of this article is twofold: first it provides the reader with an updated and exhaustive review of the most important inventory control policies to be used when dealing with products return (reverse logistics). Second, the article aims at comparing (by proposing an advanced simulation framework called IMPRES) the behaviour of different inventory control policies (in terms of supply chain costs) extending some of the models proposed in literature in different directions (i.e., disposal option available at any stage of the supply chain, stochastic manufacturing and remanufacturing lead times, multiple return options, multi-echelon inventory systems).

Integrated planning and scheduling built on cluster analysis and simulation optimisation

Abstract: This paper proposes integrated solutions for product delivery planning and scheduling in distribution centres. Cluster analysis, computer simulation and metaheuristic optimisation are applied to improve planning decisions at tactical and operational levels. An integrated approach to product delivery planning and scheduling built on integration of these technologies is described. A cluster analysis of product demand data of stores is used to identify typical dynamic demand patterns and associated product delivery tactical plans. Customer regional clusters are built through multi-objective optimisation. Metaheuristic optimisation techniques are applied to define optimal parameters of product transportation and delivery schedules. Here, vehicle scheduling is performed for the routed solution. Integrated solutions are illustrated and adjusted to a specific business case.

Simulation as enabling technologies for agile thinking: training and education aids for decision makers

Abstract: This paper describes ongoing researches and preliminary results obtained about the potential of serious games for identification, development and education of specific soft skills. These characteristics correspond to the capability to catch at glance a solid understanding of the details in a scenario or the identification of missing elements in a set of information. This paper proposes an interdisciplinary research where expertise in modelling and simulation and serious gaming are mixed with skills in education and decision-making development. The authors’ goal is to develop a methodology and a set of games that could support decision makers to develop intuition and the capability to think and understand out of personal frameworks (Baisini et al., 2010, 2011). Preliminary experimentations are proposed by using an existing serious game ‘Sibilla’. The results are also useful to direct the research where to focus the efforts for developing ad hoc games for this very specific purpose.

A parameterised model of multimodal freight transportation for maritime services optimisation

Abstract: Multimodal transport has been promoted by several transport commissions initiatives as an alternative to road transport. A key factor for improving its competitiveness is to provide private and public investors with means of evaluating and selecting the most profitable options. This paper presents a parameterisation schema of a freight transport model for the assessment of a multimodal transport service in terms of its internal rate of return (IRR). Parameterisation enables the application of optimisation algorithms to maximise the profitability. Finally, a case study consisting of the evaluation of a new maritime service for the interregional freight transport in Spain is used to verify the proposed parameterisation.

Situation awareness in critical infrastructures

Abstract: Critical infrastructure(CI) protectionand situationawarenessarerelevanttopicsin critical system domain. These issuesgofarbeyond the academicworldinvolvingvery often the national security framework. In this contribution, a review of the most attractive approaches proposed for addressing the situation awareness problems is presented. Most of the proposed approaches are based on multi-sensor data fusion, since the awareness is achieved by building a scenario using data providedby sensors spread into the systems. Humans are supposed to interact with the system, but only a few models are able to include their intervention. The review analysis is performed by considering models, architectures, and techniques adopted in each system and by highlighting their effectiveness and drawbacks. Finally an example in the field of air traffic management is presented.

Using simulation in verification of a mathematical model for predicting the performance of manual assembly line occupied with flexible workforce

Abstract: Designing a dynamic system with inherent randomness requires a predictable and dependable mathematical model accurately representing the essential aspects of real systems So it is necessary to establish a confidence level in the mathematical model of this system by carrying out a verification process for this model to collect evidence This paper deals with verification of the mathematical model designed for the prediction of performance of manual assembly lines occupied by a flexible workforce referred to as walking worker(s) assembly line (WWAL) To verify the mathematical model, it was applied to an illustrative industrial example Also experiments carried out on this example were simulated using a software package Then, the predicted results of the mathematical model were compared with simulation results Comparison leads to the verification of both the accuracy and the serviceability of the mathematical model developed

Modelling methodology for the simulation of the manufacturing systems

Abstract: Facing an increasingly competitive environment, companies must continually improve the performance of their production systems to respond to consumer demand which is increasingly unpredictable, unstable and with competitive prices This article is intended as a contribution to finding a solution to an emerging problem in the management of manufacturing flows in recent years where product diversity, shortened lead times and strong competition make the aspect of the 'flow' of goods from supplier to end customer a central one In this perspective, the aim of this paper is to develop a flexible modelling environment for the simulation and analysis of production systems This environment enables the decomposition of the production system, by offering generic and modular concepts for modelling the physical processes as well as the control processes to simulate the manufacturing processes as a whole These concepts are specified and modelled using an object oriented approach such as the unified modelling language (UML)

A modelling and simulation approach to assessment of a negative binomial approximation in a multi-echelon inventory system

Abstract: Some studies in the multi-echelon inventory systems literature have used a negative binomial distribution to approximate a critical random variable arising in the model. Graves (1996) developed a multi-echelon inventory model with fixed replenishment intervals, where each site follows a base stock policy. He proposed in the one-warehouse, N-retailer case a negative binomial distribution to approximate a random variable he referred to as ‘uncovered demand’. Computational evidence was provided to demonstrate the effectiveness of the approximation. Graves then suggested search procedures for approximately optimal base stock levels at the warehouse and N identical retailers under two customer service criteria: 1) probability of no stockout; 2) fill rate. A separate analytical evaluation of the negative binomial approximation has been preliminarily reported elsewhere. In the current study, we apply a modelling and simulation approach to assess whether the approximation-based search procedures, in fact, lead to optimal or near-optimal stock levels.

Quantitative method on miners' emergency response capacity

Abstract: To realise optimal selection of key posts and reduce human–initiated accidents in coal mines, a fuzzy comprehensive evaluation model is established for miners' emergency response capacity (ERC) together with an index system. First, a hierarchical structure that has four first–level indexes and 14 second–level indexes is constructed on account of literature dependence and safety engineering practices. Secondly, all indexes' weights are determined by means of the analytic hierarchy process (AHP), which is widely used to identify indexes' relative importance. Thirdly, the fuzzy comprehensive evaluation method based on fuzzy mathematics is used to study each index's weight distribution, and a total score is calculated in fuzzy evaluation. Finally, we take some coalmines as an example to illustrate the validity of the proposed evaluation model, and countermeasures can be put forward to improve miners' emergency capability in accordance with evaluation results.

Analysis of the operations of an intermodal barge terminal

Abstract: This paper studies the operations of intermodal barge terminals. The objective is to increase the terminal's efficiency by supporting the operational planning of the terminal operator. For this purpose, a review on general and process-specific barge terminal planning problems, discussed in current scientific literature, is provided. This theoretical knowledge is validated in practice by means of a comparison with operational planning realities at Haven Genk, a Belgian trimodal terminal. Finally, simulation studies based on Haven Genk data are performed to investigate whether vessel size and number of vessels in use have an impact on barge terminal

CFD modelling of thermal distribution in industrial server centres for configuration optimisation and energy efficiency

Abstract: The use of servers for computational and communication control tasks is becoming more and more frequent in industries and institutions. Ever increasing computational power and data storage combined with reduction in chipsets size resulted in the increased heat density and need for proper configurations of the server racks to enhance cooling and energy efficiency. While different methods can be used to model and design new server centres and optimise their configuration, there is no clear guideline in the literature on the best way to design them and how to increase energy efficiency of existing server centres. This paper presents a simplified yet reliable computational fluid dynamics (CFD) model used to qualitatively evaluate different cooling solutions of a data centre and proposes guidelines to improve its energy efficiency. The influence of different parameters and configurations on the cooling load of the server room is then analysed.

Electric vehicle industry development environment evaluation in China based on BP neural network

Abstract: As an emerging industry of energy conservation and environment protection, electric vehicle industry has broad prospects for development. But now, electric car industry is in the initial stage and the development environment is complex, so it is very necessary to study the development environment. This paper combines electric vehicle industry development environment evaluation index system with BP neural network to establish the electric vehicle industry evaluation model. Then the indicator score values as training samples obtained from the use of experts scoring method are imported to the BP neural network evaluation model. After training and testing the neural network, this paper compares the testing results with the results based on analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method, to test the validity of the evaluation model. The result shows that evaluation model based on BP neural network can effectively improve the reliability and accuracy of evaluation result.

Sample average approximation method for the chance–constrained stochastic programming in the transportation model of emergency management

Abstract: This study proposes a stochastic programming model for the transportation of emergency resource during the emergency response. Since it is difficult to predict the timing and magnitude of any disaster and its impact on the urban system, resource mobilisation is treated in a random manner, and the resource requirements are represented as random variables. Randomness is represented by the chance constraints in this paper. To deal with the difficulty in calculating the chance constraint function, we use conditional value at risk (CVaR) to approximate the chance constraint, and solve the approximation problem of the chance–constrained stochastic programming by using the sample average approximation (SAA) method. For a given sample, the SAA problem is a deterministic nonlinear programming (NLP) and any appropriate NLP code can be applied to solve the problem. The model and method provide a new way for the emergency logistics management engineering.

Evaluating policies using agent–based simulations: investigating policies for continuity of care

Abstract: Anticipating effects of proposed clinical policies is a difficult task. This study investigates the usefulness of agent–based simulations for evaluating clinical policies. Two policies for continuity of care for patients with type 2 diabetes are investigated using an agent–based simulation. Computational models of a dynamic decision environment were simulated to determine aggregated effects of individual care–providing agents acting to achieve clinical goals. The simulated policies were: 1) continuous care (CC), where each patient was randomly assigned a specific physician model for care across visits; 2) opportunistic care (OC), where each patient on each visit was randomly assigned to a physician model for treatment. These policy scenarios are at the crux of a debate as to whether continuity of care needs to be administered by a single provider or by a single organisation (e.g., clinic). The study determines under which conditions CC and OC policies result in favourable patient outcomes.

Specification of CPN models into MAS platform for the modelling of social policy issues: FUPOL project

Abstract: Simulation transparency is becoming more crucial in the decision making process when quantitative computer tools are used to justify some strategies. The coloured petri net (CPN) formalism is a promising modelling approach to foster simulation transparency by means of state space traceability tools, which have been proven to be useful for modelling system dynamics with conflict patterns. E-governance is one of these areas in which the use of a multi agent system (MAS) to represent social dynamics in a certain urban context could be used to engage citizens in the design of urban policies that affects their habitat environment. In this paper a modelling methodology to represent and analyse a context-aware multi agent-based system, which tends to be highly complex is proposed. CPN models are used to specify citizen’s preferences and affinities in front of an urban contextual change, while MAS is used to evaluate the social dynamics by translating the CPN semantic rules into agent’s rules in NetLogo.

Innovative models for supporting operational planning

Abstract: Innovative simulation models are proposed for supporting operational planning related to civil military cooperation (CIMIC) and psychological operations (PSYOPs) within complex scenarios. The paper describes these models as well as the experimentation in situations involving crisis and conflicts (i.e., Afghanistan); these models are based on the intelligent agent computer generated forces (IA-CGF) developed by simulation team and they have been extensively used in CIMIC and planning research in complex operational realistic network (CAPRICORN) project, an initiative led by University of Genoa for European Defense Agency (EDA). The proposed models take care both of logistics and operational issues as well as of the effects on the people and interest groups; indeed the paper proposes the simulator developed to demonstrate these capabilities that include the communications among the stakeholders, the population models as well as the effects of human factors including social and cultural aspects. The paper includes experimental results based on this simulator devoted to validate and test the models in strong cooperation with final users and subject matter experts (SME); the proposed experimentation is based on design of experiment techniques including mean square pure error (MSpE) and sensitivity analysis.

A prototype for project management game development using high level architecture

Abstract: Construction games teach students various concepts of managing project risks, making critical resource allocation and utilisation decisions, activity sequencing and other related construction issues. Past game development environments range from programs running monolithically on standalone computers to synthetic environments that support distributed modules (programs) running concurrently on different computers. This paper discusses one such environment, the construction synthetic environment (COSYE) based on high level architecture (HLA), which has potential as a game development environment. Then a framework for developing project management games within COSYE is proposed, based on experiences from previous game developments. Examples of games discussed include the bidding game, a tunnelling game and a crane lift planning game. This framework is meant to simplify game development. The paper highlights specifications for an administrator, a player and a simulator module.

Dynamics of software systems projects during the requirements process improvement

Abstract: Requirements process improvement (RPI) in software systems is aimed at systematically controlling changes of the requirements specification and making improvements that result in high quality specifications at reduced costs and delivered within the specified schedule. RPI activities are dynamic and complex processes managing all changes to the requirements process. Therefore, in order to meet customer and business needs, organisations need to have an effective RPI that will result into quality specifications, within a stipulated budget. This paper explores the dynamics that exists among the factors that influence a successful RPI in order to provide the understanding required to explain how the underpinning process attributes affect the quality and associated costs of the RE specification delivered to the customer. The authors contend that the developed system dynamics based RPI model is a generic decision making framework for an effective approach to RPI.

Research on probability of default prediction based on loan company's credit fund trading behaviours

Abstract: The probability of default (PD) is an important parameter to quantify credit risk, which is usually impacted by some less frequent accidents, such as market factors or the macroeconomic climate changes. The traditional approaches to estimate PD, such as expert–method or pattern classification based on a set of financial indicators, are heavily dependent on financial reports offered by borrow–customers, and can lead to unreliability and long–time lags in forecast. According to the business schema of loan–fund expenditure surveillance in some commercial banks in China, this paper proposes a support vector machine (SVM) PD classifier constructed on a set of loan–fund expenditure behaviour features, which can be directly collected from the fund trading databases of the banks in time. For the sake of comparison, both of the Logistic and SVM models are tested in this paper to predict PD, and their classification accuracy can be up to 84.6% and 89.4% respectively.