Abstract: Abu Dhabi is one of the fastest developed cities in the region. On top of all the current and future environmental challenges, Abu Dhabi aims to be among the top governments in the world in sustainable development. Abu Dhabi plans to create an attractive, livable and sustainable managed urban environment in which all necessary services and infrastructure are provided in a sustainable and timely manner. Abu Dhabi is engaged in a difficult challenge to develop credible environmental indicators that would assess the ambitious environmental targets. The aim of those indicators is to provide reliable guidance to decision makers and the public concerning key factors that determine the state of urban environment and identify major areas for policy intervention. In order to ensure sustainable development in UAE in general, and of Abu Dhabi City in particular, relevant and contextual environmental indicators need to be carefully considered. These indicators provide a gauge at a national government scale of how close countries are to establish environmental policy goals. The environment indicators assist city decision-making in such areas as identification of significant environmental aspects and observation of environmental performance trends. Those can help to find ways of reducing environmental pollution and in improving eco-efficiency. This paper outlines recent strategies implemented in Abu Dhabi that aims to improve the sustainable performance of the city-s built environment. The paper explores the variety of current and possible indicators at different levels and their roles in the development of the city.
Abstract: Land surface temperature (LST) is an important
parameter to study in urban climate. The understanding of the
influence of biophysical factors could improve the establishment of
modeling urban thermal landscape. It is well established that climate
hold a great influence on the urban landscape. However, it has been
recognize that climate has a low priority in urban planning process,
due to the complex nature of its influence. This study will focus on
the relatively cloud free Landsat Thematic Mapper image of the study
area, acquired on the 2nd March 2006. Correlation analyses were
conducted to identify the relationship of LST to the biophysical
factors; vegetation indices, impervious surface, and albedo to
investigate the variation of LST. We suggest that the results can be
considered by the stackholders during decision-making process to
create a cooler and comfortable environment in the urban landscape
for city dwellers.
Abstract: Project selection problems on management
information system (MIS) are often considered a multi-criteria
decision-making (MCDM) for a solving method. These problems
contain two aspects, such as interdependencies among criteria and
candidate projects and qualitative and quantitative factors of projects.
However, most existing methods reported in literature consider these
aspects separately even though these two aspects are simultaneously
incorporated. For this reason, we proposed a hybrid method using
analytic network process (ANP) and fuzzy logic in order to represent
both aspects. We then propose a goal programming model to conduct
an optimization for the project selection problems interpreted by a
hybrid concept. Finally, a numerical example is conducted as
verification purposes.
Abstract: In this paper, a fuzzy algorithm and a fuzzy multicriteria
decision framework are developed and used for a practical
question of optimizing biofuels policy making. The methodological
framework shows how to incorporate fuzzy set theory in a decision
process of finding a sustainable biofuels policy among several policy
options. Fuzzy set theory is used here as a tool to deal with
uncertainties of decision environment, vagueness and ambiguities of
policy objectives, subjectivities of human assessments and imprecise
and incomplete information about the evaluated policy instruments.
Abstract: Successful public-private-partnership (PPP)
implementation can not be achieved without the active participation of
private sector companies. This paper examines the decision-making of
private sector companies in public works delivered by the PPP model
on the basis of social responsibility theory. It proposes that private
sector companies should indentify objectives of entering into PPP
projects, and shoulder relevant social responsibilities, while a
minimum return should also be guaranteed in their favor, so as to
compensate for their assumed risk and support them to take on
responsibilities in the future. The paper also gives a calculation
regarding the appropriate scale and reasonable degree of private sector
involvement in PPP projects through the cost-benefit analysis in a
specific case study, with the purpose to guide the private sector
companies to create a cooperation environment resembling
“symbiosis" and facilitate the smooth implementation of public works
delivered by the PPP model.
Abstract: Bond Graph as a unified multidisciplinary tool is widely
used not only for dynamic modelling but also for Fault Detection and
Isolation because of its structural and causal proprieties. A binary
Fault Signature Matrix is systematically generated but to make the
final binary decision is not always feasible because of the problems
revealed by such method. The purpose of this paper is introducing a
methodology for the improvement of the classical binary method of
decision-making, so that the unknown and identical failure signatures
can be treated to improve the robustness. This approach consists of
associating the evaluated residuals and the components reliability data
to build a Hybrid Bayesian Network. This network is used in two
distinct inference procedures: one for the continuous part and the
other for the discrete part. The continuous nodes of the network are
the prior probabilities of the components failures, which are used by
the inference procedure on the discrete part to compute the posterior
probabilities of the failures. The developed methodology is applied
to a real steam generator pilot process.
Abstract: Quantitative methods of economic decision-making as
the methodological base of the so called operational research
represent an important set of tools for managing complex economic
systems,both at the microeconomic level and on the macroeconomic
scale. Mathematical models of controlled and controlling processes
allow, by means of artificial experiments, obtaining information
foroptimalor optimum approaching managerial decision-making.The
quantitative methods of economic decision-making usually include a
methodology known as structural analysis -an analysisof
interdisciplinary production-consumption relations.
Abstract: This paper investigates the relationship between state and business in the context of structural and institutional transformations in Indonesia following the collapse of the New Order regime in 1998. Since 1998, Indonesia has embarked on a shift from an authoritarian to democratic polity and from a centralised to a decentralised system of governance, transforming the country into the third largest democracy and one of the most decentralised states in the world. This paper examines whether the transformation of the Indonesian state has altered the pattern of state and business relations with focus on clientism and corruption as the key dependent variable, and probes how/to what extent this has changed as a result of the transformation and the ensuring shifts in business and state relations. Based on interviews with key government and business actors as well as prominent scholars in Indonesia, it is found that since the demise of the New Order, business associations in Indonesia have become more independent of state control and more influential in public decision-making whereas the government has become more responsive of business concerns and more committed to combat corruption and clientism. However, these changes have not necessarily rendered business people completely leave individualclientelistic relationship with the government, and simply pursue wider sectoral and business-wide collectivism as an alternative way of channelling their aspirations, which is expected to help reduce corruption and clientism in Indonesia. This paper concludes that democratisation and a more open politics may have helped reduce corruption and clientism in Indonesia through changes in government. However, it is still difficult to imply that such political transformation has fostered business collective action and a broader, more encompassing pattern of business lobbying and activism, which is expected to help reduce corruption and clientism.
Abstract: In the past decade, artificial neural networks (ANNs)
have been regarded as an instrument for problem-solving and
decision-making; indeed, they have already done with a substantial
efficiency and effectiveness improvement in industries and businesses.
In this paper, the Back-Propagation neural Networks (BPNs) will be
modulated to demonstrate the performance of the collaborative
forecasting (CF) function of a Collaborative Planning, Forecasting and
Replenishment (CPFR®) system. CPFR functions the balance between
the sufficient product supply and the necessary customer demand in a
Supply and Demand Chain (SDC). Several classical standard BPN will
be grouped, collaborated and exploited for the easy implementation of
the proposed modular ANN framework based on the topology of a
SDC. Each individual BPN is applied as a modular tool to perform the
task of forecasting SKUs (Stock-Keeping Units) levels that are
managed and supervised at a POS (point of sale), a wholesaler, and a
manufacturer in an SDC. The proposed modular BPN-based CF
system will be exemplified and experimentally verified using lots of
datasets of the simulated SDC. The experimental results showed that a
complex CF problem can be divided into a group of simpler
sub-problems based on the single independent trading partners
distributed over SDC, and its SKU forecasting accuracy was satisfied
when the system forecasted values compared to the original simulated
SDC data. The primary task of implementing an autonomous CF
involves the study of supervised ANN learning methodology which
aims at making “knowledgeable" decision for the best SKU sales plan
and stocks management.
Abstract: The emergence of information technology has
resulted in an ever-increasing demand to use computers for the
efficient management and dissemination of information. Keeping in
view the strong need of farmers to collect important and updated
information for interactive, flexible and quick decision-making, a
model of Decision Support System for Farm Management is
developed. The paper discusses the use of Internet technology for the
farmers to take decisions. A model is developed for the farmers to
access online interactive and flexible information for their farm
management. The workflow of the model is presented highlighting
the information transfer between different modules.
Abstract: Purpose of this paper is two-folded. At first it explains
the major problems that are causing stagnation in brownfield
redevelopment. In addition, these problems given the context of the
present multi-actor built environment are becoming more complex to
observe. Therefore, this paper suggests also a prospective decisionmaking
approach that is the most appropriate to observe and react on
the given stagnation problems. Such an approach should be regarded
as prescriptive-interactive decision-making approach, a barely
established branch. This approach should offer models that have
prescriptive as well as an interactive component enabling them to
successfully cope with the multi-actor environment. Overall, this
paper provides up-to-date insight on the brownfield stagnation by
gradually introducing the nowadays major problems and offers a
prospective decision-making approach how these problems could be
tackled.
Abstract: Food and fibre production in arid and semi-arid regions has emerged as one of the major challenges for various socio-economic and political reasons such as the food security and self-sufficiency. Productive use of the renewable water resources has risen on top ofthe decision-making agenda. For this reason, efficient operation and maintenance of modern irrigation and drainage schemes become part and parcel and indispensible reality in agricultural policy making arena. The aim of this paper is to investigate the complexity of operating and maintaining such schemes, mainly focussing on challenges which enhance and opportunities that impedsustainable food and fibre production. The methodology involved using secondary data complemented byroutine observations and stakeholders views on issues that influence the O&M in the Dez command area. The SPSS program was used as an analytical framework for data analysis and interpretation.Results indicate poor application efficiency in most croplands, much of which is attributed to deficient operation of conveyance and distribution canals. These in turn, are reportedly linked to inadequate maintenance of the pumping stations and hydraulic structures like turnouts,flumes and other control systems particularly in the secondary and tertiary canals. Results show that the aforementioned deficiencies have been the major impediment to establishing regular flow toward the farm gates which subsequently undermine application efficiency and tillage operationsat farm level. Results further show that accumulative impact of such deficiencies has been the major causes of poorcrop yield and quality that deem production system in these croplands uneconomic. Results further show that the present state might undermine the sustainability of agricultural system in the command area. The overall conclusion being that present water management is unlikely to be responsive to challenges that the sector faces. And in the absence of coherent measures to shift the status quo situation in favour of more productive resource use, it would be hard to fulfil the objectives of the National Economic and Socio-cultural Development Plans.
Abstract: A multi-agent system is developed here to predict
monthly details of the upcoming peak of the 24th solar magnetic
cycle. While studies typically predict the timing and magnitude of
cycle peaks using annual data, this one utilizes the unsmoothed
monthly sunspot number instead. Monthly numbers display more
pronounced fluctuations during periods of strong solar magnetic
activity than the annual sunspot numbers. Because strong magnetic
activities may cause significant economic damages, predicting
monthly variations should provide different and perhaps helpful
information for decision-making purposes. The multi-agent system
developed here operates in two stages. In the first, it produces twelve
predictions of the monthly numbers. In the second, it uses those
predictions to deliver a final forecast. Acting as expert agents, genetic
programming and neural networks produce the twelve fits and
forecasts as well as the final forecast. According to the results
obtained, the next peak is predicted to be 156 and is expected to
occur in October 2011- with an average of 136 for that year.
Abstract: This paper presents a multi-objective order allocation
planning problem with the consideration of various real-world
production features. A novel hybrid intelligent optimization model,
integrating a multi-objective memetic optimization process, a Monte
Carlo simulation technique and a heuristic pruning technique, is
proposed to handle this problem. Experiments based on industrial data
are conducted to validate the proposed model. Results show that (1)
the proposed model can effectively solve the investigated problem by
providing effective production decision-making solutions, which
outperformsan NSGA-II-based optimization process and an industrial
method.
Abstract: Reference point effects of top managers exerts an influence on managerial decision-making behaviors. We introduces the main idea of developing the decision behavior testing system designed for top manager in team task circumstance. According to the theory of the reference point effect, study of testing experiments in the reference point effect is carried out. Under managerial decision-making simulation environment, a platform is designed for testing reference point effect. The system uses the outcome of the value of the reference point to report the characteristics of the decision behavior of top managers.
Abstract: Decisions are regularly made during a project or
daily life. Some decisions are critical and have a direct impact on
project or human success. Formal evaluation is thus required,
especially for crucial decisions, to arrive at the optimal solution
among alternatives to address issues. According to microeconomic
theory, all people-s decisions can be modeled as indifference curves.
The proposed approach supports formal analysis and decision by
constructing indifference curve model from the previous experts-
decision criteria. These knowledge embedded in the system can be
reused or help naïve users select alternative solution of the similar
problem. Moreover, the method is flexible to cope with unlimited
number of factors influencing the decision-making. The preliminary
experimental results of the alternative selection are accurately
matched with the expert-s decisions.
Abstract: The right to housing is a basic need while good
quality and affordable housing is a reflection of a high quality of life.
However, housing remains a major problem for most, especially for
the bottom billions. Satisfaction on housing and neighbourhood
conditions are one of the important indicators that reflect quality of
life. These indicators are also important in the process of evaluating
housing policy with the objective to increase the quality of housing
and neighbourhood. The research method is purely based on a
quantitative method, using a survey. The findings show that housing
purchasing trend in urban Malaysia is determined by demographic
profiles, mainly by education level, age, gender and income. The
period of housing ownership also influenced the socio-cultural
interactions and satisfaction of house owners with their
neighbourhoods. The findings also show that the main concerns for
house buyers in urban areas are price and location of the house.
Respondents feel that houses in urban Malaysia is too expensive and
beyond their affordability. Location of houses and distance from
work place are also regarded as the main concern. However,
respondents are fairly satisfied with religious and socio-cultural
facilities in the housing areas and most importantly not many regard
ethnicity as an issue in their decision-making, when buying a house.
Abstract: This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang-s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying the proposed model to the APP problems with three scenarios of inventory levels. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple combined response levels. There has been a trend to solve complex planning problems using various metaheuristics. Therefore, in this paper, the multi-objective APP problem is solved by hybrid metaheuristics of the hunting search (HuSIHSA) and firefly (FAIHSA) mechanisms on the improved harmony search algorithm. Results obtained from the solution of are then compared. It is observed that the FAIHSA can be used as a successful alternative solution mechanism for solving APP problems over three scenarios. Furthermore, the FAIHSA provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the desirability function approach and related model parameters until a good optimal solution is obtained with proper selection of control parameters when compared.
Abstract: With the implied volatility as an important factor in
financial decision-making, in particular in option pricing valuation,
and also the given fact that the pricing biases of Leland option pricing
models and the implied volatility structure for the options are related,
this study considers examining the implied adjusted volatility smile
patterns and term structures in the S&P/ASX 200 index options using
the different Leland option pricing models. The examination of the
implied adjusted volatility smiles and term structures in the
Australian index options market covers the global financial crisis in
the mid-2007. The implied adjusted volatility was found to escalate
approximately triple the rate prior the crisis.
Abstract: Mathematical programming has been applied to various
problems. For many actual problems, the assumption that the parameters
involved are deterministic known data is often unjustified. In
such cases, these data contain uncertainty and are thus represented
as random variables, since they represent information about the
future. Decision-making under uncertainty involves potential risk.
Stochastic programming is a commonly used method for optimization
under uncertainty. A stochastic programming problem with recourse
is referred to as a two-stage stochastic problem. In this study, we
consider a stochastic programming problem with simple integer
recourse in which the value of the recourse variable is restricted to a
multiple of a nonnegative integer. The algorithm of a dynamic slope
scaling procedure for solving this problem is developed by using a
property of the expected recourse function. Numerical experiments
demonstrate that the proposed algorithm is quite efficient. The
stochastic programming model defined in this paper is quite useful
for a variety of design and operational problems.