An integrated fuzzy analytic hierarchy process and fuzzy multiple-criteria decision-making simulation approach for maintenance policy selectionAzadeh, Ali; Abdolhossein Zadeh, Saeed
doi: 10.1177/0037549715616686pmid: N/A
Selecting a proper maintenance strategy in an attempt to preclude failures is of critical significance in system engineering due to its fallbacks in the safety and economics of plants operation. This process is a typical multiple-criteria decision-making (MCDM) problem that involves both tangible and intangible parameters that are often in conflict with each other. In this paper, an integrated analytic hierarchy process (AHP)–fuzzy MCDM approach is proposed to perform a comprehensive comparison between different maintenance policies. For this purpose, various criteria are taken into account that are different in nature, as some give a crisp value obtained from simulation, some are defined in linguistic terms based on experts’ opinions and some are in the form of triangular fuzzy numbers. The AHP method is used to determine the importance weights of the criteria. Subsequently, a distance-based fuzzy MCDM approach is employed to rank different maintenance policies and select the most appropriate one. Moreover, the fuzzy technique for the order of prioritization by similarity to ideal solution is used for verification of the proposed integrated approach. Lastly, the impact of each criterion on the rankings is examined. Four commonly implemented maintenance policies, namely condition-based, time-based, failure-based and opportunistic, are considered in this study. Also, a real-world example is presented to demonstrate the applicability of the proposed approach. The most significant feature of this approach lies in its capability in incorporating data in the forms of linguistic variables, triangular fuzzy numbers and crisp numbers into the evaluation process.
Distributed multi-scale muscle simulation in a hybrid MPI–CUDA computational environmentIvanović, Miloš; Stojanović, Boban; Kaplarević-Mališić, Ana; Gilbert, Richard; Mijailovich, Srboljub
doi: 10.1177/0037549715620299pmid: N/A
We present Mexie, an extensible and scalable software solution for distributed multi-scale muscle simulations in a hybrid MPI–CUDA environment. Since muscle contraction relies on the integration of physical and biochemical properties across multiple length and time scales, these models are highly processor and memory intensive. Existing parallelization efforts for accelerating multi-scale muscle simulations imply the usage of expensive large-scale computational resources, which produces overwhelming costs for the everyday practical application of such models. In order to improve the computational speed within a reasonable budget, we introduce the concept of distributed calculations of multi-scale muscle models in a mixed CPU–GPU environment. The concept is applied to a two-scale muscle model, in which a finite element macro model is coupled with the microscopic Huxley kinetics model. Finite element calculations of a continuum macroscopic model take place strictly on the CPU, while numerical solutions of the partial differential equations of Huxley’s cross-bridge kinetics are calculated on both CPUs and GPUs. We present a modular architecture of the solution, along with an internal organization and a specific load balancer that is aware of memory boundaries in such a heterogeneous environment. Solution was verified on both benchmark and real-world examples, showing high utilization of involved processing units, ensuring high scalability. Speed-up results show a boost of two orders of magnitude over any previously reported distributed multi-scale muscle models. This major improvement in computational feasibility of multi-scale muscle models paves the way for new discoveries in the field of muscle modeling and future clinical applications.
Simulation of the competition among traditional and on-demand software vendorsCocco, Luisanna; Concas, Giulio; Marchesi, Michele
doi: 10.1177/0037549715620502pmid: N/A
In this work, we propose a simulation model to study the software market, and in particular the competition among on-premise and on-demand vendors of customer relationship management software. In this market two kinds of vendors, on-premise and on-demand vendors, and corporate customers interact. Vendors have an initial capital and a specific number of developers. They invest a fraction of their capital in their product quality and try to sell their products making a profit. Corporate customers buy software products for their employees, trying to minimize their cost and maximize their utility. The proposed model is able to reproduce the real trends of the market as regards both the price of software and the market shares of the vendors, despite there is relatively little empirical evidence available about the various mechanisms at play, and few experimental data. Our model could be used as a tool to forecast future market trends, or to plan business policies of investment and pricing. Any firm could calibrate this model depending on its past business trends in order to obtain simple guidelines to follow in the planning of business winning strategies.
Real-time simulation and performance analysis of multimachine power systems using dSPACE simulatorRamya, R; Selvi, K; Murali, K
doi: 10.1177/0037549715620014pmid: N/A
The analysis of the characteristics of multiple machines constituting a power system in real time is of paramount importance. The reported work uses dSPACE, a dynamic simulator, in investigating the characteristics of the said multimachine system. The transient model of the Western System Coordinating Council (WSCC) nine-bus, three-unit system is developed using MATLAB/Simulink. Using real-time interface, the model is executed in the digital signal processor (DSP) of dSPACE hardware. The model is analyzed for its performance against multiple changes in mechanical torque and load variation. The transient behavior of the model upon incidence of a significant network fault and its robustness towards to perturbations in network and system parameters are thoroughly analyzed. The conditions are emulated by usage of the digital signal processor and DS1104 Controller Board.
Simulating police containment of a protest crowdPosadas, Vector Ion; Teknomo, Kardi
doi: 10.1177/0037549715621388pmid: N/A
This paper presents an agent-based computational model of the crowd containment tactic known as kettling, which involves cordons of police officers surrounding a crowd of protesters in order to restrict its movement. Our model uses steering behavior techniques to simulate a series of simple scenarios in which an unorganized group of protester agents clash with an opposing group of police agents holding position in a stationary, multiple-rank line formation. We investigate the stability and penetrability of the police formation and how they are influenced by the formation’s thickness (number of layers) as well as the specific behavioral strategy employed by individual police agents—whether using global or local references, or combinations of both. Our results show that a strategy using purely global references produces optimal performance, while increasing the number of formation layers enables strategies using combined references to approach this optimum to different degrees.