148,498 research outputs found
Analytical Evaluation of Hierarchical Planning Systems
Hierarchical planning systems have become popular for multilevel decision problems. After reviewing the concept of hierarchical planning and citing some examples, the authors describe a method for analytic evaluation of a hierarchical planning system. They show that multilevel decision problems can be nicely modeled as multistage stochastic programs. Then any hierarchical planning system can be measured against the yardstick of optimality in this stochastic program. They demonstrate this approach on a hierarchical system that can be shown to be asymptotically optimal for a job shop design/scheduling problem
Development of the Integrated Model of the Automotive Product Quality Assessment
Issues on building an integrated model of the automotive product quality assessment are studied herein basing on widely applicable methods and models of the quality assessment. A conceptual model of the automotive product quality system meeting customer requirements has been developed. Typical characteristics of modern industrial production are an increase in the production dynamism that determines the product properties; a continuous increase in the volume of information required for decision-making, an increased role of knowledge and high technologies implementing absolutely new scientific and technical ideas. To solve the problem of increasing the automotive product quality, a conceptual structural and hierarchical model is offered to ensure its quality as a closed system with feedback between the regulatory, manufacturing, and information modules, responsible for formation of the product quality at all stages of its life cycle. The three module model of the system of the industrial product quality assurance is considered to be universal and to give the opportunity to explore processes of any complexity while solving theoretical and practical problems of the quality assessment and prediction for products for various purposes, including automotive
Analysis of Green Computing Strategy in University: Analytic Network Process (ANP) Approach
Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis do not provide an analytical means to determine the importance of the identified factors of green computing strategy and implementation. Although the SWOT analysis successfully explores the factors, individual factors are usually described very generally. For this reason, SWOT analysis possesses deficiencies in the measurement and evaluation of green computing steps. Even though the analytic hierarchy process (AHP) technique eliminates these deficiencies, it does not allow for measuring the possible dependencies among the individual factors. The AHP method assumes that the green computing factors presented in the hierarchical structure are independent; however, this assumption may be inappropriate in light of certain situation. Therefore, it is important to utilize a form of SWOT analysis that calculates and takes into account the possible dependency among the factors. This paper demonstrates a process for quantitative SWOT analysis of green computing implementation that can be performed even when there is dependence among strategic factors. The proposed algorithm uses the analytic network process (ANP), which allows measurement of the dependency among the green computing implementation factors, as well as AHP, which is based on the independence between the factors. There are four alternatives: campus awareness program, computer procurement, increase in heat removal requirement, and increase in equipment power density for improving the implementation of green computing in campus. Dependency among the SWOT factors is observed to effect the strategic and sub-factor weights, as well as to change the strategy priorities. Based on ANC method, the best alternative for this implementation is computer procurement
Prospects of a mathematical theory of human behavior in complex man-machine systems tasks
A hierarchy of human activities is derived by analyzing automobile driving in general terms. A structural description leads to a block diagram and a time-sharing computer analogy. The range of applicability of existing mathematical models is considered with respect to the hierarchy of human activities in actual complex tasks. Other mathematical tools so far not often applied to man machine systems are also discussed. The mathematical descriptions at least briefly considered here include utility, estimation, control, queueing, and fuzzy set theory as well as artificial intelligence techniques. Some thoughts are given as to how these methods might be integrated and how further work might be pursued
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids
Real-life control tasks involve matters of various substances---rigid or soft
bodies, liquid, gas---each with distinct physical behaviors. This poses
challenges to traditional rigid-body physics engines. Particle-based simulators
have been developed to model the dynamics of these complex scenes; however,
relying on approximation techniques, their simulation often deviates from
real-world physics, especially in the long term. In this paper, we propose to
learn a particle-based simulator for complex control tasks. Combining learning
with particle-based systems brings in two major benefits: first, the learned
simulator, just like other particle-based systems, acts widely on objects of
different materials; second, the particle-based representation poses strong
inductive bias for learning: particles of the same type have the same dynamics
within. This enables the model to quickly adapt to new environments of unknown
dynamics within a few observations. We demonstrate robots achieving complex
manipulation tasks using the learned simulator, such as manipulating fluids and
deformable foam, with experiments both in simulation and in the real world. Our
study helps lay the foundation for robot learning of dynamic scenes with
particle-based representations.Comment: Accepted to ICLR 2019. Project Page: http://dpi.csail.mit.edu Video:
https://www.youtube.com/watch?v=FrPpP7aW3L
A framework for the selection of the right nuclear power plant
Civil nuclear reactors are used for the production of electrical energy. In the nuclear industry vendors propose several nuclear reactor designs with a size from 35–45 MWe up to 1600–1700 MWe. The choice of the right design is a multidimensional problem since a utility has to include not only financial factors as levelised cost of electricity (LCOE) and internal rate of return (IRR), but also the so called “external factors” like the required spinning reserve, the impact on local industry and the social acceptability. Therefore it is necessary to balance advantages and disadvantages of each design during the entire life cycle of the plant, usually 40–60 years. In the scientific literature there are several techniques for solving this multidimensional problem. Unfortunately it does not seem possible to apply these methodologies as they are, since the problem is too complex and it is difficult to provide consistent and trustworthy expert judgments. This paper fills the gap, proposing a two-step framework to choosing the best nuclear reactor at the pre-feasibility study phase. The paper shows in detail how to use the methodology, comparing the choice of a small-medium reactor (SMR) with a large reactor (LR), characterised, according to the International Atomic Energy Agency (2006), by an electrical output respectively lower and higher than 700 MWe
- …