17,669 research outputs found
Employing dynamic fuzzy membership functions to assess environmental performance in the supplier selection process
The proposed system illustrates that logic fuzzy can be used to aid management in assessing a supplier's environmental performance in the supplier selection process. A user-centred hierarchical system employing scalable fuzzy membership functions implement human priorities in the supplier selection process, with particular focus on a supplier's environmental performance. Traditionally, when evaluating supplier performance, companies have considered criteria such as price, quality, flexibility, etc. These criteria are of varying importance to individual companies pertaining to their own specific objectives. However, with environmental pressures increasing, many companies have begun to give more attention to environmental issues and, in particular, to their suppliers’ environmental performance. The framework presented here was developed to introduce efficiently environmental criteria into the existing supplier selection process and to reflect on its relevant importance to individual companies. The system presented attempts to simulate the human preference given to particular supplier selection criteria with particular focus on environmental issues when considering supplier selection. The system considers environmental data from multiple aspects of a suppliers business, and based on the relevant impact this will have on a Buying Organization, a decision is reached on the suitability of the supplier. This enables a particular supplier's strengths and weaknesses to be considered as well as considering their significance and relevance to the Buying OrganizationPeer reviewe
Subjective Versus Objective Economic Measures, A fuzzy logic exercise
It is rather evident that there is much more (statistical) information about objective aggregates, such as inflation, output or unemployment than that concerning subjective aggregates, such as well-being, satisfaction, confidence or even expectations. Due to its characteristics, fuzzy logic can and should indeed be used to understand how some of those subjective measures can be approximated by objective ones. This task is accomplished in the paper by the use of Portuguese data on consumer confidence - the subjective economic measure - and on the unemployment rate - the objective economic measure -. The results clearly indicate that to be a worthwhile exercise as the clear importance of unemployment on confidence is only revealed by the fuzzy logic approximation
FURY: Fuzzy unification and resolution based on edit distance
We present a theoretically founded framework for fuzzy
unification and resolution based on edit distance over trees.
Our framework extends classical unification and resolution
conservatively. We prove important properties of the framework
and develop the FURY system, which implements the
framework efficiently using dynamic programming. We
evaluate the framework and system on a large problem in
the bioinformatics domain, that of detecting typographical
errors in an enzyme name databas
Platform Relative Sensor Abstractions across Mobile Robots using Computer Vision and Sensor Integration
Uniform sensor management and abstraction across different robot platforms is a difficult task due to the sheer diversity of sensing devices. However, because these sensors can be grouped into categories that in essence provide the same information, we can capture their similarities and create abstractions. An example would be distance data measured by an assortment of range sensors, or alternatively extracted from a camera using image processing. This paper describes how using software components it is possible to uniformly construct high-level abstractions of sensor information across various robots in a way to support the portability of common code that uses these abstractions (e.g. obstacle avoidance, wall following). We demonstrate our abstractions on a number of robots using different configurations of range sensors and cameras
Parametric optimization of the femoropopliteal artery stent design based on numerical analysis
High-failure rates of Peripheral Arterial Disease (PAD) stenting were reported due to
the inability of certain stent strut configuration to accommodate severe biomechanical
environment of the Femoro-Popliteal Artery (FPA) such as bends, twists, and axially
compresses during limb flexion. The unique of mechanical deformation environment
in FPA has been considered one of main factors affecting the durability of the FPA
stent and reducing the stent life. Consequently, various optimization techniques have
been developed to improve the mechanical performance of the FPA stent. The present
work shown that, the first-two of twelve FPA resemble stent models stent models have
been selected with a net score of 3.65 Model I and, with a net score of 3.55 Model II
via applying Pictorial Selection Method. Finite Element Method (FEM) of
optimization study based-parameterization has been conducted for stent strut
dimensions, stents were compared in terms of force-stress behavior. Multi Criteria
Decision Making (MCDM) method has been utilized to identify the best combination
of strut dimensions. The strut thickness parameterization results were in relation T α
1/σ (T is strut thickness) for both models with all mechanical loading modes.
Moreover, the strut width parameterization results were in relation W α 1/σ (W is strut
width) for both models with all mechanical loading modes. Whereas, the strut length
parameterization results were in relation L α σ in case of Model I and, L α 1/σ (L is
strut length) in case of Model II, under axial loads, while under three-point bending
and torsion loading modes L α σ for both models, under radial compression the
relations were L α 1/σ in case of Model I and, L α σ in case of Model II. The best
combination of strut dimension in the thickness case was t4 = 230 µm for both models,
in strut width were w3=0.180, and w4= 0.250 mm for Model I and Model II,
respectively, and in strut length were l2= 1.40, and l2= 1.75 mm for Model I and Model
II, respectively. In conclusions, the mathematical selection approach and the consistent
mathematical approach of MCDM has been proposed, also the mechanical
performance has been improved for parameterized stent models
Development, test and comparison of two Multiple Criteria Decision Analysis(MCDA) models: A case of healthcare infrastructure location
When planning a new development, location decisions have always been a major issue. This paper examines and compares two modelling methods used to inform a healthcare infrastructure location decision. Two Multiple Criteria Decision Analysis (MCDA) models were developed to support the optimisation of this decision-making process, within a National Health Service (NHS) organisation, in the UK. The proposed model structure is based on seven criteria (environment and safety, size, total cost, accessibility, design, risks and population profile) and 28 sub-criteria. First, Evidential Reasoning (ER) was used to solve the model, then, the processes and results were compared with the Analytical Hierarchy Process (AHP). It was established that using ER or AHP led to the same solutions. However, the scores between the alternatives were significantly different; which impacted the stakeholders‟ decision-making. As the processes differ according to the model selected, ER or AHP, it is relevant to establish the practical and managerial implications for selecting one model or the other and providing evidence of which models best fit this specific environment. To achieve an optimum operational decision it is argued, in this study, that the most transparent and robust framework is achieved by merging ER process with the pair-wise comparison, an element of AHP. This paper makes a defined contribution by developing and examining the use of MCDA models, to rationalise new healthcare infrastructure location, with the proposed model to be used for future decision. Moreover, very few studies comparing different MCDA techniques were found, this study results enable practitioners to consider even further the modelling characteristics to ensure the development of a reliable framework, even if this means applying a hybrid approach
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