Abstract: In the multi objective optimization, in the case when generated set of Pareto optimal solutions is large, occurs the problem to select of the best solution from this set. In this paper, is suggested a method to order of Pareto set. Ordering the Pareto optimal set carried out in conformity with the introduced distance function between each solution and selected reference point, where the reference point may be adjusted to represent the preferences of a decision making agent. Preference information about objective weights from a decision maker may be expressed imprecisely. The developed elicitation procedure provides an opportunity to obtain surrogate numerical weights for the objectives, and thus, to manage impreciseness of preference. The proposed method is a scalable to many objectives and can be used independently or as complementary to the various visualization techniques in the multidimensional case.
Abstract: Recent developments in storage technology and
networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate
decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is
logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among
concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data
streams.
Abstract: The structure of retinal vessels is a prominent feature,
that reveals information on the state of disease that are reflected in
the form of measurable abnormalities in thickness and colour.
Vascular structures of retina, for implementation of clinical diabetic
retinopathy decision making system is presented in this paper.
Retinal Vascular structure is with thin blood vessel, whose accuracy
is highly dependent upon the vessel segmentation. In this paper the
blood vessel thickness is automatically detected using preprocessing
techniques and vessel segmentation algorithm. First the capture
image is binarized to get the blood vessel structure clearly, then it is
skeletonised to get the overall structure of all the terminal and
branching nodes of the blood vessels. By identifying the terminal
node and the branching points automatically, the main and branching
blood vessel thickness is estimated. Results are presented and
compared with those provided by clinical classification on 50 vessels
collected from Bejan Singh Eye hospital..
Abstract: Data Envelopment Analysis (DEA) is a methodology
that computes efficiency values for decision making units (DMU) in a
given period by comparing the outputs with the inputs. In many cases,
there are some time lag between the consumption of inputs and the
production of outputs. For a long-term research project, it is hard to
avoid the production lead time phenomenon. This time lag effect
should be considered in evaluating the performance of organizations.
This paper suggests a model to calculate efficiency values for the
performance evaluation problem with time lag. In the experimental
part, the proposed methods are compared with the CCR and an
existing time lag model using the data set of the 21st century frontier
R&D program which is a long-term national R&D program of Korea.
Abstract: A human verification system is presented in this
paper. The system consists of several steps: background subtraction,
thresholding, line connection, region growing, morphlogy, star
skelatonization, feature extraction, feature matching, and decision
making. The proposed system combines an advantage of star
skeletonization and simple statistic features. A correlation matching
and probability voting have been used for verification, followed by a
logical operation in a decision making stage. The proposed system
uses small number of features and the system reliability is
convincing.
Abstract: This paper proposes a new decision making approch
based on quantitative possibilistic influence diagrams which are
extension of standard influence diagrams in the possibilistic framework.
We will in particular treat the case where several expert
opinions relative to value nodes are available. An initial expert assigns
confidence degrees to other experts and fixes a similarity threshold
that provided possibility distributions should respect. To illustrate our
approach an evaluation algorithm for these multi-source possibilistic
influence diagrams will also be proposed.
Abstract: In recent years, environment regulation forcing
manufactures to consider recovery activity of end-of- life products
and/or return products for refurbishing, recycling,
remanufacturing/repair and disposal in supply chain management. In
this paper, a mathematical model is formulated for single product
production-inventory system considering remanufacturing/reuse of
return products and rate of return products follows a demand like
function, dependent on purchasing price and acceptance quality level.
It is useful in decision making to determine whether to go for
remanufacturing or disposal of returned products along with newly
produced products to satisfy a stationary demand. In addition, a
modified genetic algorithm approach is proposed, inspired by particle
swarm optimization method. Numerical analysis of the case study is
carried out to validate the model.
Abstract: Public administration institutions in cooperation with
politicians are not the sole policy decision makers in full meaning
any longer. Meanwhile, a special role, namely steering the decision
making process, could be delegated to them.
Despite the wide scientific discussion on different aspects what
has direct impact on policy creation, there is a lack of holistic
practical managerial advice, which could integrate infrastructure of
policy decision making with intellectual capital and with
interconnection of partnership. The proposed harmonized decision
making model of process, people and partnership entitled by
acronym HM-3P is analyzed as a framework for implementation of
public administration steering role seeking the coherent social
involvement in policy decision making.
Abstract: Chemical industry project management involves
complex decision making situations that require discerning abilities
and methods to make sound decisions. Project managers are faced
with decision environments and problems in projects that are
complex. In this work, case study is Research and Development
(R&D) project selection. R&D is an ongoing process for forward
thinking technology-based chemical industries. R&D project
selection is an important task for organizations with R&D project
management. It is a multi-criteria problem which includes both
tangible and intangible factors. The ability to make sound decisions
is very important to success of R&D projects. Multiple-criteria
decision making (MCDM) approaches are major parts of decision
theory and analysis. This paper presents all of MCDM approaches
for use in R&D project selection. It is hoped that this work will
provide a ready reference on MCDM and this will encourage the
application of the MCDM by chemical engineering management.
Abstract: Despite of many scholars and practitioners recognize
the knowledge management implementation in an organizations but
insufficient attention has been paid by researchers to select suitable
knowledge portal system (KPS) selection. This study develops a
Multi Criteria Decision making model based on the fuzzy VIKOR
approach to help organizations in selecting KPS. The suitable portal
is the critical influential factors on the success of knowledge
management (KM) implementation in an organization.
Abstract: Trust management and Reputation models are
becoming integral part of Internet based applications such as CSCW,
E-commerce and Grid Computing. Also the trust dimension is a
significant social structure and key to social relations within a
collaborative community. Collaborative Decision Making (CDM) is
a difficult task in the context of distributed environment (information
across different geographical locations) and multidisciplinary
decisions are involved such as Virtual Organization (VO). To aid
team decision making in VO, Decision Support System and social
network analysis approaches are integrated. In such situations social
learning helps an organization in terms of relationship, team
formation, partner selection etc. In this paper we focus on trust
learning. Trust learning is an important activity in terms of
information exchange, negotiation, collaboration and trust
assessment for cooperation among virtual team members. In this
paper we have proposed a reinforcement learning which enhances the
trust decision making capability of interacting agents during
collaboration in problem solving activity. Trust computational model
with learning that we present is adapted for best alternate selection of
new project in the organization. We verify our model in a multi-agent
simulation where the agents in the community learn to identify
trustworthy members, inconsistent behavior and conflicting behavior
of agents.
Abstract: This study examines the possibility to apply the theory of multidimensional accounting (momentum accounting) in a Brazilian Navy-s Services Provider Military Organization (Organização Militar Prestadora de Serviços - OMPS). In general, the core of the said theory is the fact that Accounting does not recognize the inertia of transactions occurring in an entity, and that occur repeatedly in some cases, regardless of the implementation of new actions by its managers. The study evaluates the possibility of greater use of information recorded in the financial statements of the unit of analysis, within the strategic decisions of the organization. As a research strategy, we adopted the case study. The results infer that it is possible to use the theory in the context of a multidimensional OMPS, promoting useful information for decision-making and thereby contributing to the strengthening of the necessary alignment of its administration with the current desires of the Brazilian society.
Abstract: Recent theorizations on the cognitive process of moral
judgment have focused on the role of intuitions and emotions, marking
a departure from previous emphasis on conscious, step-by-step
reasoning. My study investigated how being in a disgusted mood state
affects moral judgment.
Participants were induced to enter a disgusted mood state through
listening to disgusting sounds and reading disgusting descriptions.
Results shows that they, when compared to control who have not been
induced to feel disgust, are more likely to endorse actions that are
emotionally aversive but maximizes utilitarian return
The result is analyzed using the 'emotion-as-information' approach
to decision making. The result is consistent with the view that
emotions play an important role in determining moral judgment.
Abstract: The rapid growth of e-Commerce services is
significantly observed in the past decade. However, the method to
verify the authenticated users still widely depends on numeric
approaches. A new search on other verification methods suitable for
online e-Commerce is an interesting issue. In this paper, a new online
signature-verification method using angular transformation is
presented. Delay shifts existing in online signatures are estimated by
the estimation method relying on angle representation. In the
proposed signature-verification algorithm, all components of input
signature are extracted by considering the discontinuous break points
on the stream of angular values. Then the estimated delay shift is
captured by comparing with the selected reference signature and the
error matching can be computed as a main feature used for verifying
process. The threshold offsets are calculated by two types of error
characteristics of the signature verification problem, False Rejection
Rate (FRR) and False Acceptance Rate (FAR). The level of these two
error rates depends on the decision threshold chosen whose value is
such as to realize the Equal Error Rate (EER; FAR = FRR). The
experimental results show that through the simple programming,
employed on Internet for demonstrating e-Commerce services, the
proposed method can provide 95.39% correct verifications and 7%
better than DP matching based signature-verification method. In
addition, the signature verification with extracting components
provides more reliable results than using a whole decision making.
Abstract: Decision making preferences to certain criteria
usually focus on positive degrees without considering the negative
degrees. However, in real life situation, evaluation becomes more
comprehensive if negative degrees are considered concurrently.
Preference is expected to be more effective when considering both
positive and negative degrees of preference to evaluate the best
selection. Therefore, the aim of this paper is to propose the
conflicting bifuzzy preference relations in group decision making by
utilization of a novel score function. The conflicting bifuzzy
preference relation is obtained by introducing some modifications on
intuitionistic fuzzy preference relations. Releasing the intuitionistic
condition by taking into account positive and negative degrees
simultaneously and utilizing the novel score function are the main
modifications to establish the proposed preference model. The
proposed model is tested with a numerical example and proved to be
simple and practical. The four-step decision model shows the
efficiency of obtaining preference in group decision making.
Abstract: Teachers form the backbone of any educational system, hence selecting qualified candidates is very crucial. In Malaysia, the decision making in the selection process involves a few stages: Initial filtering through academic achievement, taking entry examination and going through an interview session. The last stage is the most challenging since it highly depends on human judgment. Therefore, this study sought to identify the selection criteria for teacher candidates that form the basis for an efficient multi-criteria teacher-candidate selection model for that last stage. The relevant criteria were determined from the literature and also based on expert input that is those who were involved in interviewing teacher candidates from a public university offering the formal training program. There are three main competency criteria that were identified which are content of knowledge, communication skills and personality. Further, each main criterion was divided into a few subcriteria. The Analytical Hierarchy Process (AHP) technique was employed to allocate weights for the criteria and later, integrated a Simple Weighted Average (SWA) scoring approach to develop the selection model. Subsequently, a web-based Decision Support System was developed to assist in the process of selecting the qualified teacher candidates. The Teacher-Candidate Selection (TeCaS) system is able to assist the panel of interviewers during the selection process which involves a large amount of complex qualitative judgments.
Abstract: Currently, the Malaysian construction industry is
focusing on transforming construction processes from conventional
building methods to the Industrialized Building System (IBS). Still,
research on the decision making of IBS technology adoption with the
influence of contextual factors is scarce. The purpose of this paper is
to explore how contextual factors influence the IBS decision making
in building projects which is perceived by those involved in
construction industry namely construction stakeholders and IBS
supply chain members. Theoretical background, theoretical
frameworks and literatures which identify possible contextual factors
that influence decision making towards IBS technology adoption are
presented. This paper also discusses the importance of contextual
factors in IBS decision making, highlighting some possible crossover
benefits and making some suggestions as to how these can be
utilized. Conclusions are drawn and recommendations are made with
respect to the perception of socio-economic, IBS policy and IBS
technology associated with building projects.
Abstract: Knowing consumers' preferences and perceptions of
the sensory evaluation of drink products are very significant to
manufacturers and retailers alike. With no appropriate sensory
analysis, there is a high risk of market disappointment. This paper
aims to rank the selected coffee products and also to determine the
best of quality attribute through sensory evaluation using fuzzy
decision making model. Three products of coffee drinks were used
for sensory evaluation. Data were collected from thirty judges at a
hypermarket in Kuala Terengganu, Malaysia. The judges were asked
to specify their sensory evaluation in linguistic terms of the quality
attributes of colour, smell, taste and mouth feel for each product and
also the weight of each quality attribute. Five fuzzy linguistic terms
represent the quality attributes were introduced prior analysing. The
judgment membership function and the weights were compared to
rank the products and also to determine the best quality attribute. The
product of Indoc was judged as the first in ranking and 'taste' as the
best quality attribute. These implicate the importance of sensory
evaluation in identifying consumers- preferences and also the
competency of fuzzy approach in decision making.
Abstract: Nowadays, the plant location selection has a critical
impact on the performance of numerous companies. In this paper, a
methodology is presented to solve this problem. The three decision
making methods, namely Delphi, AHP and improved VIKOR, are
hybridized in order to make the best use of information available
based on the decision makers or experts. In this respect, the aim of
using Delphi is to select the most influential criteria by a few decision
makers. The AHP is utilized to give weights of the selected criteria.
Finally, the improved VIKOR method is applied to rank alternatives.
At the end of paper, an application example demonstrates the
applicability of the proposed methodology.
Abstract: Main goal of preventive healthcare problems are at
decreasing the likelihood and severity of potentially life-threatening
illnesses by protection and early detection. The levels of
establishment and staffing costs along with summation of the travel
and waiting time that clients spent are considered as objectives
functions of the proposed nonlinear integer programming model. In
this paper, we have proposed a bi-objective mathematical model for
designing a network of preventive healthcare facilities so as to
minimize aforementioned objectives, simultaneously. Moreover, each
facility acts as M/M/1 queuing system. The number of facilities to be
established, the location of each facility, and the level of technology
for each facility to be chosen are provided as the main determinants
of a healthcare facility network. Finally, to demonstrate performance
of the proposed model, four multi-objective decision making
techniques are presented to solve the model.