Predetermined intervals for start times of activities in?the?stochastic project scheduling problem

This paper proposes a new methodology to schedule activities in projects with stochastic activity durations. The main idea is to determine for each activity an interval in which the activity is allowed to start its processing. Deviations from these intervals result in penalty costs. We employ the Cross-Entropy methodology to set the intervals so as to minimize the sum of the expected penalty costs. The paper describes the implementation of the method, compares its results to other heuristic methods and provides some insights towards actual applications.     

Social indicators and policy selection: An experiment in constructing a social objective function

A small scale experiment is described, the main purpose of which is to evaluate methodology for evaluating within group and between group differences in attitude to a range of scenarios constructed from a number of social and economic indicators. Three countries featured in the study, Greece, Holland, and the U.K. The tool employed in the multidimensional analysis of preference judgements was the suite of linear programming techniques (linmap) developed during the 1970's by Srinivasan and Shocker. It is concluded that the methodology is feasible and could have more general application.     

Dynamic modelling and performance study of solar gas tunnel dryer

The work presented in this article focuses on the analysis and modelling of heat and mass transfers in the tunnel dryer during the drying of agricultural products. The main objective of this work is to establish a global modelling of the studied system based on the bond graph methodology. The pseudo-bond graph methodology was used in modelling the system. Such methodology was very suitable for this thermal process since it allows good management of the nonlinearity present in the system.

The thermal performance of the proposed dryer is analysed by solving the various energy balance equations. An application of drying tomatoes was achieved and a fair agreement was observed between predicted and experimental results.     

Numerical investigation of the deformation characteristics and heat generation in pneumatic aircraft tires : Part I. Mechanical modeling

A numerical methodology to study the temperature rise in aircraft tires under free rolling conditions is presented in this article. In the first part, we study the deformation characteristics of the tire to determine the heat generation due to the inelastic deformation (viscoelasticity), which is assumed to be the main source of heat generation under free rolling conditions. The heat generation is then used as an input to solve the heat transfer problem which is addressed in the second part of this article. A methodology which considers a 2-D formulation with the contribution of out-of-plane forces is presented. This methodology allows for a significant reduction of the computational requirements of 3-D analysis while capturing the main 3-D effects. The deformation pattern as well as the stress and strain fields are presented for a cross-section of the tire at several locations.     

A fuzzy approach to R&D project portfolio selection

A major advance in the development of project selection tools came with the application of options reasoning in the field of Research and Development (R&D). The options approach to project evaluation seeks to correct the deficiencies of traditional methods of valuation through the recognition that managerial flexibility can bring significant value to projects. Our main concern is how to deal with non-statistical imprecision we encounter when judging or estimating future cash flows. In this paper, we develop a methodology for valuing options on R&D projects, when future cash flows are estimated by trapezoidal fuzzy numbers. In particular, we present a fuzzy mixed integer programming model for the R&D optimal portfolio selection problem, and discuss how our methodology can be used to build decision support tools for optimal R&D project selection in a corporate environment.     

Bayesian Copulae Distributions, with Application to Operational Risk Management

The aim of this paper is to introduce a new methodology for operational risk management, based on Bayesian copulae. One of the main problems related to operational risk management is understanding the complex dependence structure of the associated variables. In order to model this structure in a flexible way, we construct a method based on copulae. This allows us to split the joint multivariate probability distribution of a random vector of losses into individual components characterized by univariate marginals. Thus, copula functions embody all the information about the correlation between variables and provide a useful technique for modelling the dependency of a high number of marginals. Another important problem in operational risk modelling is the lack of loss data. This suggests the use of Bayesian models, computed via simulation methods and, in particular, Markov chain Monte Carlo. We propose a new methodology for modelling operational risk and for estimating the required capital. This methodology combines the use of copulae and Bayesian models.      

Estudio probabilista del daño por choque según la metodología PEER. Aplicación a un paso superior sísmicamente aislado

Bridges with deck supported either on sliding or elastomeric bearings are common in mid-seismicity regions. Pounding between deck and abutments is linked with their main seismic vulnerabilities, which can be assessed by estimating the probability of a given state of damage being reached in a given time period. This paper presents a state of the art methodology used to solve that problem, as well as its application to the assessment of the vulnerability of an overpass placed in Granada area (South-east of Spain), belonging to the previously mentioned typology.The Pacific Earthquake Engineering Research Center methodology will be adapted and applied. Their main steps will be briefly presented, although the identification and characterization of damage likely to occur will be described in more detail. The model of the structure, and specially pounding modeling, will also be detailed.Results are interesting since this bridge can be considered as a representative of a widespread class. The adapted methodology may be applied to similar structures. Also, probability values obtained may serve as benchmarks.     

Extending the range of player-performance measures in one-day cricket

The author's previous paper on this topic showed that the Duckworth/Lewis methodology has considerable potential for providing relevant and objective measures of performance in one-day cricket. The present paper evaluates how these measures can apply in the longer term. This assessment is based upon several series of matches involving the main players from most of the major cricketing nations. Although data used are not exhaustive, they are of sufficient quantity to provide strong indications of the long-term viability of the measures, thus leading to the realistic expectation of inclusion of the methodology into the existing player-rankings or the development of an independent set of performance indicators that reflect more validly the value of players' inputs to matches. Such measures are expected to be of valuable use to team management, media commentators and to the public.     

Meta-control of an interacting-particle algorithm for global optimization

A common issue for stochastic global optimization algorithms is how to set the parameters of the sampling distribution (e.g. temperature, mutation/cross-over rates, selection rate, etc.) so that the samplings converge to the optimum effectively and efficiently. We consider an interacting-particle algorithm and develop a meta-control methodology which analytically guides the inverse temperature parameter of the algorithm to achieve desired performance characteristics (e.g. quality of the final outcome, algorithm running time, etc.). The main aspect of our meta-control methodology is to formulate an optimal control problem where the fractional change in the inverse temperature parameter is the control variable. The objectives of the optimal control problem are set according to the desired behavior of the interacting-particle algorithm. The control problem considers particles’ average behavior, rather than treating the behavior of individual particles. The solution to the control problem provides feedback on the inverse temperature parameter of the algorithm.     

Prioritization of organizational capital measurement indicators using fuzzy AHP

Organizational capital is a sub-dimension of the intellectual capital which is the sum of all assets that make the creative ability of the organization possible. To control and manage such an important force, the companies must measure it first. This study aims at defining a methodology to improve the quality of prioritization of organizational capital measurement indicators under uncertain conditions. To do so, a methodology based on the extent fuzzy analytic hierarchy process (AHP) is applied. Within the model, three main attributes; deployment of the strategic values, investment to the technology and flexibility of the structure; their sub-attributes and 10 indicators are defined. To define the priority of each indicator, preferences of experts are gathered using a pair-wise comparison based questionnaire. The results of the study show that “deployment of the strategic values” is the most important attribute of the organizational capital.     

Methodology for selecting packaging alternatives: an “action research” application in the industrial sector

Packaging could and should be considered one of the key elements that promote supply chain performance in terms of efficiency and sustainability. Although, packaging should be considered as a system comprising three different levels (primary, secondary and tertiary), in the industrial sphere design problems are usually centered exclusively on two levels: the primary packaging (the “box”) and the tertiary packaging (the “unit load”). Thus, the main object of this paper is to propose a methodology that facilitates, in a comprehensive way, decision making in packaging system design in order to reduce total costs. To do so, the methodology makes a qualitative and quantitative exploration (including a proposal of a heuristic method) to establish strategies that enable the definition, comparison and selection of an efficient range of package designs (with their associated dimensions) that is efficient and sustainable in an overall way in terms of purchasing costs, logistics costs and environmental costs. Likewise, the authors develop the successful case of a Spanish company implementing successfully the proposed methodology. To develop this case, the authors have adopted an “Action Research” approach. The empirical validation process was developed over almost 10 years.

     

High-frequency response of a calculation methodology for gas dynamics based on Independent Time Discretisation

A calculation methodology to solve the one-dimensional governing equations system is presented. This calculation methodology is based on the Independent Time Discretisation (ITD) of the ducts composing the system. The purpose is the improvement of the trade-off between the accuracy and the computational cost that the current 1D gas dynamic models can yield. The ITD methodology is applied to the specific problem of noise prediction in internal combustion engines in order to evaluate its performance in the frequency domain. The application of the ITD methodology to the well-known acoustic configurations which are representative of the main attenuation mechanisms in commercial mufflers shows its ability. The potential is evaluated in terms of reduction of the computational cost and the accuracy and robustness provided by the results as a function of the spatial mesh size and the family of finite difference numerical method applied.     

Tracking customer portfolio composition: A factor analysis approach

In this paper, we address the changing composition of a customer portfolio taking into account actions undertaken by the company to adapt its service offer to market conditions and/or technological innovations. We present a specific methodology to identify clusters of customers in different periods and then compare them over time. The classification process takes into account both qualitative and quantitative aspects of the consumption levels of the services or products offered by the company. The possibility of period‐to‐period variation in the customer portfolio and the service or product offer is also considered, in order to achieve a more realistic scenario. The core of the proposed methodology is related to the family of exploratory factorial and cluster techniques. The customers are classified by using a bicriterial clustering methodology based on ‘tandem’ analysis (multiple factor analysis+cluster analysis of the main factors). The bicriterial approach allows for a compromise between customers' consumption levels (a quantitative criterion) and their consumption/non‐consumption pattern (a qualitative criterion). The evolution of the customer portfolio composition is explored through multiple correspondence analysis. This technique allows visual comparison of the position of different clusters against time and the identification of key changes in customer consumption behavior. The methodology is tested on realistic customer portfolio scenarios for a major telecommunication company. We simulate various scenarios to show the strengths of our proposal. Copyright © 2009 John Wiley & Sons, Ltd.     

Modelling variations in hospital service delivery based on real time locating information

Variations in service delivery have been identified as a major challenge to the success of process improvement studies in service departments of hospital such as radiology. Largely, these variations are due to inherent system level factors, i.e., system variations such as unavailability of resources (nurse, bed, doctors, and equipment). These system variations are largely unnecessary/unwarranted and mostly lead to longer waiting times, delays, and lowered productivity of the service units. There is limited research on identifying system variations and modelling them for service improvements within hospital. Therefore, this paper proposes a modelling methodology to model system variations in radiology based on real time locating system (RTLS) tracking data. The methodology employs concepts from graph theory to identify and represent system variations. In particular, edge coloured directed multi-graphs (ECDMs) are used to model system variations which are reflected in paths adopted by staff, i.e., sequence of rooms/areas traversed while delivering services. The main steps of the methodology are: (i) identifying the most standard path followed by staff for service delivery; (ii) filtering the redundant events in RTLS tracking database for analysis; (iii) identifying rooms/areas of hospital site involved in the service delivery; (iv) determining patterns of paths adopted by staff from filtered tracking database; and, (v) representation of patterns in graph based model called as edge coloured directed multigraphs (ECDMs) of a role. A case study of MR scanning process is utilized to illustrate the implementation of the proposed methodology for modelling system variations reflected in the paths adopted by staff.     

CFD studies on the surge detection of a radial compressor flow by analyzing the unsteady secondary flow field

The objective of this investigation is the development of a reliable methodology allowing the accurate prediction of compressor surge. In this context a centrifugal compressor used in a commercial application with five main and five splitter blades, installed in regular passenger vehicles, is numerically analyzed. For this purpose a CFD analysis is conducted. The steady-state and unsteady secondary flow field is analyzed and studied by a frequency analysis to detect critical oscillations. (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Object-oriented Design of Reusable Model Libraries of Hybrid Dynamic Systems – Part Two: A Case Study

A novel object-oriented methodology for the design of model libraries is exemplified by means of the design of JARA. JARA is a set of libraries of dynamic hybrid models of some fundamental physical-chemical principles. Its main application field is the modeling of physical-chemical processes in the context of automatic control. Only a reduced set of phenomena has been selected for modeling, focusing mainly on illustrating relevant aspects of the proposed design methodology. The five steps of the design methodology are followed and the design rules of JARA are obtained.     

Reasoning under uncertainty with FIR methodology

The aim of this research is to develop a new methodology called UNFIR (uncertainty in FIR) as an extension of the fuzzy inductive reasoning (FIR) technique. The main idea behind UNFIR is to expand the modeling capacity of the FIR methodology allowing it to work with classical fuzzy rules. On the one hand, UNFIR is able to automatically construct fuzzy rules starting from a set of pattern rules obtained by FIR. On the other hand, UNFIR affords the prediction of systems behavior by using a mixed pattern/fuzzy inference system that takes advantage of the uncertainty inherent to the data. The pattern rule base that the FIR methodology generates can be very large, obstructing the prediction process and reducing its efficiency. The new methodology preserves as much as possible the knowledge of the pattern rules in a compact fuzzy rule base. In this process some precision is lost but the robustness is considerably increased.The performance of UNFIR methodology as a systems’ prediction tool is also studied in this work. Three different applications are used for this purpose, i.e., a linear system, a non-linear system and an industrial process.     

Fuzzy part coding for group technology

Contemporary Group Technology (GT) methods apply coding schemes as a popular method for capturing the design and manufacturing information pertinent to the parts to be grouped. Coding schemes are very popular and many different coding systems are commercially available. The main disadvantage of current coding systems, however, is their generality and lack of informative representation of the parts.This paper presents a new methodology for coding parts using fuzzy codes. The methodology is general and applies to attributes that have a crisp value (e.g., “length”, “ratio of length to diameter”), an interval value (e.g., “tolerance”, “surface roughness”) or a fuzzy value (e.g., “primary shape”). The methodology considers the range of attributes' values relevant for the grouping, and therefore, is tuned and adjusted to the specific collection of parts of interest. This method creates a more informative coding scheme which leads to improved variant process planning methods, scheduling and inventory control as well as other manufacturing functions that utilize GT.     

The effect of environmental parameters on product recovery

Economical and environmental issues are the main driving forces for the development of closed-loop supply chains. This paper examines the impact of environmental issues on long-term behaviour of a single product supply chain with product recovery. The environmental issues examined are the firm's `green image' effect on customer demand, the take back obligation imposed by legislation, and the state campaigns for proper disposal of used products. The behaviour of the system is analyzed through a dynamic simulation model based on the principles of the system dynamics (SD) methodology. This model includes all major inventories of new, used and recovered products and the flows among them. Inventory levels and flow rates are linked through differential equations. The dynamic model provides an experimental simulation tool, which can be used to evaluate the effect of environmental issues on long-term decision making in collection and remanufacturing activities and on product demand. Numerical analysis illustrates the potential uses of the methodology.     

A hybrid fuzzy-optimization approach to customer grouping-based logistics distribution operations

This paper presents an integrated fuzzy-optimization customer grouping based logistics distribution methodology for quickly responding to a variety of customer demands. The proposed methodology involves three main mechanisms: (1) pre-route customer classification using fuzzy clustering techniques, (2) determination of customer group-based delivery service priority and (3) en-route goods delivery using multi-objective optimization programming methods. In the process of pre-route customer classification, the proposed method groups customers’ orders primarily based on the multiple attributes of customer demands, rather than by static geographic attributes, which are mainly considered in classical vehicle routing algorithms. Numerical studies including a real-world application are conducted to illustrate the applicability of the proposed method and its potential advantages over existing operational strategies. Using the proposed method, it is shown that the overall performance of a logistics distribution system can be improved by more than 20%, according to the numerical results from the case studied.