Abstract: This paper discusses the role and importance of Information and Communication Technologies (ICT) and social Networking (SN) in the process of decision making for Flood Risk and Knowledge Management Strategies. We use Mozambique Red Cross (CVM) as the case study and further more we address scenarios for flood risk management strategies, using earlier warning and social networking and we argue that a sustainable desirable stage of life can be achieved by developing scenario strategic planning based on backcasting.
Abstract: The paper proposes an approach to ranking a set of potential countries to invest taking into account the investor point of view about importance of different economic indicators. For the goal, a ranking algorithm that contributes to rational decision making is proposed. The described algorithm is based on combinatorial optimization modeling and repeated multi-criteria tasks solution. The final result is list of countries ranked in respect of investor preferences about importance of economic indicators for investment attractiveness. Different scenarios are simulated conforming to different investors preferences. A numerical example with real dataset of indicators is solved. The numerical testing shows the applicability of the described algorithm. The proposed approach can be used with any sets of indicators as ranking criteria reflecting different points of view of investors.
Abstract: The paper describes an approach for defining of k-best night vision devices based on multi-criteria mixed-integer optimization modeling. The parameters of night vision devices are considered as criteria that have to be optimized. Using different user preferences for the relative importance between parameters different choice of k-best devices can be defined. An ideal device with all of its parameters at their optimum is used to determine how far the particular device from the ideal one is. A procedure for evaluation of deviation between ideal solution and k-best solutions is presented. The applicability of the proposed approach is numerically illustrated using real night vision devices data. The proposed approach contributes to quality of decisions about choice of night vision devices by making the decision making process more certain, rational and efficient.
Abstract: Value-based group decision is very complicated since many parties involved. There are different concern caused by differing preferences, experiences, and background. Therefore, a support system is required to enable each stakeholder to evaluate and rank the solution alternatives before engaging into negotiation with the other stakeholders. The support system is based on combination between value-based analysis, multi criteria group decision making based on satisfying options, and negotiation process based on coalition formation. This paper presents the group decision and negotiation on the selection of suitable material for a support bridge structure involving three decision makers, who are an estate manager, a project manager, and an engineer. There are three alternative solutions for the material of the support bridge structure, which are (a1) steel structure, (a2) reinforced concrete structure and (a3) wooden structure.
Abstract: Decentralized Tuple Space (DTS) implements tuple
space model among a series of decentralized hosts and provides the
logical global shared tuple repository. Replication has been introduced
to promote performance problem incurred by remote tuple access. In
this paper, we propose a replication approach of DTS allowing
replication policies self-adapting. The accesses from users or other
nodes are monitored and collected to contribute the decision making.
The replication policy may be changed if the better performance is
expected. The experiments show that this approach suitably adjusts the
replication policies, which brings negligible overhead.
Abstract: This paper provides an overview of auction theory literature. We present a general review on literature of various auctions and focus ourselves specifically on an English auction. We are interested in modelling bidder's behavior in an English auction environment. And hence, we present an overview of the New Zealand wool auction followed by a model that would describe a bidder's decision making behavior from the New Zealand wool auction. The mathematical assumptions in an English auction environment are demonstrated from the perspective of the New Zealand wool auction.
Abstract: Post-disaster reconstruction projects offer
opportunities to facilitate physical, social and economic development
and to reduce future hazard vulnerability long after the disasters.
Sustainability of post-disaster reconstruction project conducted in the
villages of Dinar following the 1995 earthquake was investigated in
this paper. Officials of the Government who were involved in the
project were interviewed. Besides, two field surveys were done in 12
villages of Dinar in winter months of 2008. Beneficiaries were
interviewed and physical, socio-cultural and economic impacts of the
reconstruction were examined. The research revealed that the postdisaster
reconstruction project has negative aspects from the point
view of sustainability. The physical, socio-cultural and economic
factors were not considered during decision making process of the
project.
Abstract: Creation and maintenance of knowledge management
systems has been recognized as an important research area.
Consecutively lack of accurate results from knowledge management
systems limits the organization to apply their knowledge
management processes. This leads to a failure in getting the right
information to the right people at the right time thus followed by a
deficiency in decision making processes. An Intranet offers a
powerful tool for communication and collaboration, presenting data
and information, and the means that creates and shares knowledge,
all in one easily accessible place. This paper proposes an archetype
describing how a knowledge management system, with the support
of intranet capabilities, could very much increase the accuracy of
capturing, storing and retrieving knowledge based processes thereby
increasing the efficiency of the system. This system will expect a
critical mass of usage, by the users, for intranet to function as
knowledge management systems. This prototype would lead to a
design of an application that would impose creation and maintenance
of an effective knowledge management system through intranet. The
aim of this paper is to introduce an effective system to handle
capture, store and distribute knowledge management in a form that
may not lead to any failure which exists in most of the systems. The
methodology used in the system would require all the employees, in
the organization, to contribute the maximum to deliver the system to
a successful arena. The system is still in its initial mode and thereby
the authors are under the process to practically implement the ideas,
as mentioned in the system, to produce satisfactory results.
Abstract: Building condition assessment is a critical activity in Malaysia-s Comprehensive Asset Management Model. It is closely related to building performance that impact user-s life and decision making. This study focuses on public primary school, one of the most valuable assets for the country. The assessment was carried out based on CSP1 Matrix in Kuching Division of Sarawak, Malaysia. Based on the matrix used, three main criteria of the buildings has successfully evaluate: the number of defects; schools rating; and total schools rating. The analysis carried out on 24 schools found that the overall 4, 725 defects has been identified. Meanwhile, the overall score obtained was 45, 868 and the overall rating is 9.71, which is at the fair condition. This result has been associated with building age to evaluate its impacts on school buildings condition. The findings proved that building condition is closely related to building age and its support the theory that 'the ageing building has more defect than the new one'.
Abstract: Urban problems are problems of organized complexity. Thus, many models and scientific methods to resolve urban problems are failed. This study is concerned with proposing of a fuzzy system driven approach for classification and solving urban problems. The proposed study investigated mainly the selection of the inputs and outputs of urban systems for classification of urban problems. In this research, five categories of urban problems, respect to fuzzy system approach had been recognized: control, polytely, optimizing, open and decision making problems. Grounded Theory techniques were then applied to analyze the data and develop new solving method for each category. The findings indicate that the fuzzy system methods are powerful processes and analytic tools for helping planners to resolve urban complex problems. These tools can be successful where as others have failed because both incorporate or address uncertainty and risk; complexity and systems interacting with other systems.
Abstract: We present the induced generalized hybrid
averaging (IGHA) operator. It is a new aggregation operator
that generalizes the hybrid averaging (HA) by using
generalized means and order inducing variables. With this
formulation, we get a wide range of mean operators such as
the induced HA (IHA), the induced hybrid quadratic
averaging (IHQA), the HA, etc. The ordered weighted
averaging (OWA) operator and the weighted average (WA)
are included as special cases of the HA operator. Therefore,
with this generalization we can obtain a wide range of
aggregation operators such as the induced generalized OWA
(IGOWA), the generalized OWA (GOWA), etc. We further
generalize the IGHA operator by using quasi-arithmetic
means. Then, we get the Quasi-IHA operator. Finally, we also
develop an illustrative example of the new approach in a
financial decision making problem. The main advantage of the
IGHA is that it gives a more complete view of the decision
problem to the decision maker because it considers a wide
range of situations depending on the operator used.
Abstract: The management of the health-care wastes is one of
the most important problems in Istanbul, a city with more than 12
million inhabitants, as it is in most of the developing countries.
Negligence in appropriate treatment and final disposal of the healthcare
wastes can lead to adverse impacts to public health and to the
environment. This paper employs a fuzzy multi-criteria group
decision making approach, which is based on the principles of fusion
of fuzzy information, 2-tuple linguistic representation model, and
technique for order preference by similarity to ideal solution
(TOPSIS), to evaluate health-care waste (HCW) treatment
alternatives for Istanbul. The evaluation criteria are determined
employing nominal group technique (NGT), which is a method of
systematically developing a consensus of group opinion. The
employed method is apt to manage information assessed using multigranularity
linguistic information in a decision making problem with
multiple information sources. The decision making framework
employs ordered weighted averaging (OWA) operator that
encompasses several operators as the aggregation operator since it
can implement different aggregation rules by changing the order
weights. The aggregation process is based on the unification of
information by means of fuzzy sets on a basic linguistic term set
(BLTS). Then, the unified information is transformed into linguistic
2-tuples in a way to rectify the problem of loss information of other
fuzzy linguistic approaches.
Abstract: The many feasible alternatives and conflicting
objectives make equipment selection in materials handling a
complicated task. This paper presents utilizing Monte Carlo (MC)
simulation combined with the Analytic Hierarchy Process (AHP) to
evaluate and select the most appropriate Material Handling
Equipment (MHE). The proposed hybrid model was built on the base
of material handling equation to identify main and sub criteria critical
to MHE selection. The criteria illustrate the properties of the material
to be moved, characteristics of the move, and the means by which the
materials will be moved. The use of MC simulation beside the AHP
is very powerful where it allows the decision maker to represent
his/her possible preference judgments as random variables. This will
reduce the uncertainty of single point judgment at conventional AHP,
and provide more confidence in the decision problem results. A small
business pharmaceutical company is used as an example to illustrate
the development and application of the proposed model.
Abstract: Along with the progress of our information society,
various risks are becoming increasingly common, causing multiple social problems. For this reason, risk communications for
establishing consensus among stakeholders who have different
priorities have become important. However, it is not always easy for the decision makers to agree on measures to reduce risks based on
opposing concepts, such as security, privacy and cost. Therefore, we previously developed and proposed the “Multiple Risk Communicator" (MRC) with the following functions: (1) modeling
the support role of the risk specialist, (2) an optimization engine, and (3) displaying the computed results. In this paper, MRC program
version 1.0 is applied to the personal information leakage problem. The application process and validation of the results are discussed.
Abstract: In practice, we often come across situations where it is
necessary to make decisions based on incomplete or uncertain data.
In control systems it may be due to the unknown exact mathematical
model, or its excessive complexity (e.g. nonlinearity) when it is
necessary to simplify it, respectively, to solve it using a rule base. In
the case of databases, searching data we compare a similarity
measure with of the requirements of the selection with stored data,
where both the select query and the data itself may contain vague
terms, for example in the form of linguistic qualifiers. In this paper,
we focus on the processing of uncertain data in databases and
demonstrate it on the example multi-criteria decision making in the
selection of variants, specified by higher number of technical
parameters.
Abstract: We present a method for the selection of students
in interdisciplinary studies based on the hybrid averaging
operator. We assume that the available information given in
the problem is uncertain so it is necessary to use interval
numbers. Therefore, we suggest a new type of hybrid
aggregation called uncertain induced generalized hybrid
averaging (UIGHA) operator. It is an aggregation operator
that considers the weighted average (WA) and the ordered
weighted averaging (OWA) operator in the same formulation.
Therefore, we are able to consider the degree of optimism of
the decision maker and grades of importance in the same
approach. By using interval numbers, we are able to represent
the information considering the best and worst possible results
so the decision maker gets a more complete view of the
decision problem. We develop an illustrative example of the
proposed scheme in the selection of students in
interdisciplinary studies. We see that with the use of the
UIGHA operator we get a more complete representation of the
selection problem. Then, the decision maker is able to
consider a wide range of alternatives depending on his
interests. We also show other potential applications that could
be used by using the UIGHA operator in educational problems
about selection of different types of resources such as
students, professors, etc.
Abstract: This paper aimed to study the factors that relate to
working behavior of employees at Pakkred Municipality, Nonthaburi
Province. A questionnaire was utilized as the tool in collecting
information. Descriptive statistics included frequency, percentage,
mean and standard deviation. Independent- sample t- test, analysis of
variance and Pearson Correlation were also used. The findings of this
research revealed that the majority of the respondents were female,
between 25- 35 years old, married, with a Bachelor degree. The
average monthly salary of respondents was between 8,001- 12,000
Baht, and having about 4-7 years of working experience. Regarding
the overall working motivation factors, the findings showed that
interrelationship, respect, and acceptance were ranked as highly
important factors, whereas motivation, remunerations & welfare,
career growth, and working conditions were ranked as moderately
important factors. Also, overall working behavior was ranked as high.
The hypotheses testing revealed that different genders had a
different working behavior and had a different way of working as a
team, which was significant at the 0.05 confidence level, Moreover,
there was a difference among employees with different monthly
salary in working behavior, problem- solving and decision making,
which all were significant at the 0.05 confidence level. Employees
with different years of working experience were found to have work
working behavior both individual and as a team at the statistical
significance level of 0.01 and 0.05. The result of testing the
relationship between motivation in overall working revealed that
interrelationship, respect and acceptance from others, career growth,
and working conditions related to working behavior at a moderate
level, while motivation in performing duties and remunerations and
welfares related to working behavior towards the same direction at a
low level, with a statistical significance of 0.01.
Abstract: We introduce an extended resource leveling model that abstracts real life projects that consider specific work ranges for each resource. Contrary to traditional resource leveling problems this model considers scarce resources and multiple objectives: the minimization of the project makespan and the leveling of each resource usage over time. We formulate this model as a multiobjective optimization problem and we propose a multiobjective genetic algorithm-based solver to optimize it. This solver consists in a two-stage process: a main stage where we obtain non-dominated solutions for all the objectives, and a postprocessing stage where we seek to specifically improve the resource leveling of these solutions. We propose an intelligent encoding for the solver that allows including domain specific knowledge in the solving mechanism. The chosen encoding proves to be effective to solve leveling problems with scarce resources and multiple objectives. The outcome of the proposed solvers represent optimized trade-offs (alternatives) that can be later evaluated by a decision maker, this multi-solution approach represents an advantage over the traditional single solution approach. We compare the proposed solver with state-of-art resource leveling methods and we report competitive and performing results.
Abstract: One of the biggest problems of SMEs is their tendencies to financial distress because of insufficient finance background. In this study, an Early Warning System (EWS) model based on data mining for financial risk detection is presented. CHAID algorithm has been used for development of the EWS. Developed EWS can be served like a tailor made financial advisor in decision making process of the firms with its automated nature to the ones who have inadequate financial background. Besides, an application of the model implemented which covered 7,853 SMEs based on Turkish Central Bank (TCB) 2007 data. By using EWS model, 31 risk profiles, 15 risk indicators, 2 early warning signals, and 4 financial road maps has been determined for financial risk mitigation.
Abstract: Mobile agents are a powerful approach to develop distributed systems since they migrate to hosts on which they have the resources to execute individual tasks. In a dynamic environment like a peer-to-peer network, Agents have to be generated frequently and dispatched to the network. Thus they will certainly consume a certain amount of bandwidth of each link in the network if there are too many agents migration through one or several links at the same time, they will introduce too much transferring overhead to the links eventually, these links will be busy and indirectly block the network traffic, therefore, there is a need of developing routing algorithms that consider about traffic load. In this paper we seek to create cooperation between a probabilistic manner according to the quality measure of the network traffic situation and the agent's migration decision making to the next hop based on decision tree learning algorithms.