Abstract: Economic Load Dispatch (ELD) is a method of determining
the most efficient, low-cost and reliable operation of a power
system by dispatching available electricity generation resources to
supply load on the system. The primary objective of economic
dispatch is to minimize total cost of generation while honoring
operational constraints of available generation resources. In this paper
an intelligent water drop (IWD) algorithm has been proposed to
solve ELD problem with an objective of minimizing the total cost of
generation. Intelligent water drop algorithm is a swarm-based natureinspired
optimization algorithm, which has been inspired from natural
rivers. A natural river often finds good paths among lots of possible
paths in its ways from source to destination and finally find almost
optimal path to their destination. These ideas are embedded into
the proposed algorithm for solving economic load dispatch problem.
The main advantage of the proposed technique is easy is implement
and capable of finding feasible near global optimal solution with
less computational effort. In order to illustrate the effectiveness of
the proposed method, it has been tested on 6-unit and 20-unit test
systems with incremental fuel cost functions taking into account the
valve point-point loading effects. Numerical results shows that the
proposed method has good convergence property and better in quality
of solution than other algorithms reported in recent literature.
Abstract: In this paper an ant colony optimization algorithm is
developed to solve the permutation flow shop scheduling problem. In
the permutation flow shop scheduling problem which has been vastly
studied in the literature, there are a set of m machines and a set of n
jobs. All the jobs are processed on all the machines and the sequence
of jobs being processed is the same on all the machines. Here this
problem is optimized considering two criteria, makespan and total
flow time. Then the results are compared with the ones obtained by
previously developed algorithms. Finally it is visible that our
proposed approach performs best among all other algorithms in the
literature.
Abstract: Stock portfolio selection is a classic problem in finance,
and it involves deciding how to allocate an institution-s or an individual-s
wealth to a number of stocks, with certain investment objectives
(return and risk). In this paper, we adopt the classical Markowitz
mean-variance model and consider an additional common realistic
constraint, namely, the cardinality constraint. Thus, stock portfolio
optimization becomes a mixed-integer quadratic programming problem
and it is difficult to be solved by exact optimization algorithms.
Chemical Reaction Optimization (CRO), which mimics the molecular
interactions in a chemical reaction process, is a population-based
metaheuristic method. Two different types of CRO, named canonical
CRO and Super Molecule-based CRO (S-CRO), are proposed to solve
the stock portfolio selection problem. We test both canonical CRO
and S-CRO on a benchmark and compare their performance under
two criteria: Markowitz efficient frontier (Pareto frontier) and Sharpe
ratio. Computational experiments suggest that S-CRO is promising
in handling the stock portfolio optimization problem.
Abstract: This paper is to clarify the relationship of individual investor types, risk tolerance and herding bias. The questionnaire survey investigation is conducted to collect 389 valid and voluntary individual investors and to examine how the risk tolerance plays as a mediator between four types of personality and herding bias. Based on featuring BB&K model and reviewing the prior literature of psychology, a linear structural model are constructed and further used to evaluate the path of herding formation through the analysis of Structural Equation Modeling (SEM). The results showed that more impetuous investors would be prone to herding bias directly, but rather exhibit higher risk tolerance. However, risk tolerance would fully mediate between the level of confidence (i.e., confident or anxious) and herding bias, but not mediate between the method of action (careful or impetuous) for individual investors.
Abstract: A product development for green logistics model using
the fuzzy analytic network process method is presented for evaluating
the relationships among the product design, the manufacturing
activities, and the green supply chain. In the product development
stage, there can be alternative ways to design the detailed components
to satisfy the design concept and product requirement. In different
design alternative cases, the manufacturing activities can be different.
In addition, the manufacturing activities can affect the green supply
chain of the components and product. In this research, a fuzzy analytic
network process evaluation model is presented for evaluating the
criteria in product design, manufacturing activities, and green supply
chain. The comparison matrices for evaluating the criteria among the
three groups are established. The total relational values between the
three groups represent the relationships and effects. In application, the
total relational values can be used to evaluate the design alternative
cases for decision-making to select a suitable design case and the green
supply chain. In this presentation, an example product is illustrated. It
shows that the model is useful for integrated evaluation of design and
manufacturing and green supply chain for the purpose of product
development for green logistics.
Abstract: Customarily, the LMTD correction factor, FT, is used
to screen alternative designs for a heat exchanger. Designs with
unacceptably low FT values are discarded. In this paper, authors have
proposed a more fundamental criterion, based on feasibility of a
multipass exchanger as the only criteria, followed by economic
optimization. This criterion, coupled with asymptotic energy targets,
provide the complete optimization space in a heat exchanger network
(HEN), where cost-optimization of HEN can be performed with only
Heat Recovery Approach temperature (HRAT) and number-of-shells
as variables.
Abstract: B2E portals represent a new class of web-based
information technologies which many organisations are introducing
in recent years to stay in touch with their distributed workforces and
enable them to perform value added activities for organisations.
However, actual usage of these emerging systems (measured using
suitable instruments) has not been reported in the contemporary
scholarly literature. We argue that many of the instruments to
measure usage of various types of IT-enabled information systems
are not directly applicable for B2E portals because they were
developed for the context of traditional mainframe and PC-based
information systems. It is therefore important to develop a new
instrument for web-based portal technologies aimed at employees. In
this article, we report on the development and initial qualitative
evaluation of an instrument that seeks to operationaise a set of
independent factors affecting the usage of portals by employees. The
proposed instrument is useful to IT/e-commerce researchers and
practitioners alike as it enhances their confidence in predicting
employee usage of portals in organisations.
Abstract: As a primitive assumption, if a new information
system is able to remind users their old work habits, it should have a
better opportunity to be accepted, adopted and finally, utilized. In
this paper some theoretical concepts borrowed from psychodynamic
theory e.g. ego defenses are discussed to show how such resemblance
can be made without necessarily affecting the performance of the
new system. The main assertion is a new system should somehow
imitate old work habits, not literally, but through following their
paces in terms of the order of habitual tensional states including
stimulation, defensive actions and satisfactions.
Abstract: Studying literature theme in the fields of tourism and
sustainable development and its importance in today world and their
criteria in architecture, here in this article we will also study the area
where the selected site is located; beside the Aab-Ask Village located
in Larijan region in Mazandaran province on the way to Haraz – one
of the tourism routes of Iran. After these studies by analyzing the
site, its strong potentials – such as mineral water springs (hot
springs), geothermal, landscapes and ideal climate - as a tourist
attraction spot in the region, and considering sustainable
development criteria – with regard to limits and available facilities –
a plan was offered that could change the region to provide the needs
of local people and in addition change it to a place where tourism
services is offered to the visitors and make it an acceptable sample of
stable building in Iran. Finally the reason to make design for this
complex is recovery of natural and historical values of Aab-Ask area
regarding development and sustainable architecture criteria in the
form of a functional sample which can be a suitable place to fulfill
this goal for having lots of strong points in attracting cultural and
sustainable tourist.
Abstract: In this paper the behavior of the decision feedback
equalizers (DFEs) adapted by the decision-directed or the constant
modulus blind algorithms is presented. An analysis of the error
surface of the corresponding criterion cost functions is first
developed. With the intention of avoiding the ill-convergence of the
algorithm, the paper proposes to modify the shape of the cost
function error surface by using a soft decision instead of the hard
one. This was shown to reduce the influence of false decisions and to
smooth the undesirable minima. Modified algorithms using the soft
decision during a pseudo-training phase with an automatic switch to
the properly tracking phase are then derived. Computer simulations
show that these modified algorithms present better ability to avoid
local minima than conventional ones.
Abstract: Fish-feed is a major cost component of operating expenses for any aquaculture farm. Due to soaring prices of fish-feed ingredients, the need for better feeding schedule management has become imperative. On such factor that influences the utilization rate of fish-feed are sea currents. Up to now, practical monitoring of fishfeed loss due to sea currents is not exercised. This paper gives a description of an economic methodology that aims at quantifying the amount of fish-feed lost due to sea currents and draws on data from a Mediterranean aquaculture farm to formulate the associated model.
Abstract: The most influential programming paradigm today
is object oriented (OO) programming and it is widely used in
education and industry. Recognizing the importance of equipping
students with OO knowledge and skills, it is not surprising that most
Computer Science degree programs offer OO-related courses. How
do we assess whether the students have acquired the right objectoriented
skills after they have completed their OO courses? What are
object oriented skills? Currently none of the current assessment
techniques would be able to provide this answer. Traditional forms of
OO programming assessment provide a ways for assigning numerical
scores to determine letter grades. But this rarely reveals information
about how students actually understand OO concept. It appears
reasonable that a better understanding of how to define and assess
OO skills is needed by developing a criterion referenced model. It is
even critical in the context of Malaysia where there is currently a
growing concern over the level of competency of Malaysian IT
graduates in object oriented programming. This paper discussed the
approach used to develop the criterion-referenced assessment model.
The model can serve as a guideline when conducting OO
programming assessment as mentioned. The proposed model is
derived by using Goal Questions Metrics methodology, which helps
formulate the metrics of interest. It concluded with a few suggestions
for further study.
Abstract: Intelligent systems are required in order to quickly and accurately analyze enormous quantities of data in the Internet environment. In intelligent systems, information extracting processes can be divided into supervised learning and unsupervised learning. This paper investigates intelligent clustering by unsupervised learning. Intelligent clustering is the clustering system which determines the clustering model for data analysis and evaluates results by itself. This system can make a clustering model more rapidly, objectively and accurately than an analyzer. The methodology for the automatic clustering intelligent system is a multi-agent system that comprises a clustering agent and a cluster performance evaluation agent. An agent exchanges information about clusters with another agent and the system determines the optimal cluster number through this information. Experiments using data sets in the UCI Machine Repository are performed in order to prove the validity of the system.
Abstract: In the present work, we propose a new method for
solving the matrix equation AXB=F . The new method can
be considered as a generalized form of the well-known global full
orthogonalization method (Gl-FOM) for solving multiple linear
systems. Hence, the method will be called extended Gl-FOM (EGl-
FOM). For implementing EGl-FOM, generalized forms of block
Krylov subspace and global Arnoldi process are presented. Finally,
some numerical experiments are given to illustrate the efficiency of
our new method.
Abstract: This paper presents the results related to the
interference reduction technique in multistage multiuser detector for
asynchronous DS-CDMA system. To meet the real-time
requirements for asynchronous multiuser detection, a bit streaming,
cascade architecture is used. An asynchronous multiuser detection
involves block-based computations and matrix inversions. The paper
covers iterative-based suboptimal schemes that have been studied to
decrease the computational complexity, eliminate the need for matrix
inversions, decreases the execution time, reduces the memory
requirements and uses joint estimation and detection process that
gives better performance than the independent parameter estimation
method. The stages of the iteration use cascaded and bits processed
in a streaming fashion. The simulation has been carried out for
asynchronous DS-CDMA system by varying one parameter, i.e.,
number of users. The simulation result exhibits that system gives
optimum bit error rate (BER) at 3rd stage for 15-users.
Abstract: The Minimum Weighted Vertex Cover (MWVC) problem is a classic graph optimization NP - complete problem. Given an undirected graph G = (V, E) and weighting function defined on the vertex set, the minimum weighted vertex cover problem is to find a vertex set S V whose total weight is minimum subject to every edge of G has at least one end point in S. In this paper an effective algorithm, called Support Ratio Algorithm (SRA), is designed to find the minimum weighted vertex cover of a graph. Computational experiments are designed and conducted to study the performance of our proposed algorithm. Extensive simulation results show that the SRA can yield better solutions than other existing algorithms found in the literature for solving the minimum vertex cover problem.
Abstract: This paper describes the design and modeling
procedure of a novel 5-phase segment type switched reluctance motor
(ST-SRM) under simultaneous two-phase (bipolar) excitation of
windings. The rotor cores of ST-SRM are embedded in an aluminum
block as well as to improve the performance characteristics. The
magnetic circuit of the produced ST-SRM is constructed so that the
magnetic flux paths are short and exclusive to each phase, thereby
minimizing the commutation switching and eddy current losses in the
laminations. The design and simulation principles presented apply
primarily to conventional SRM and ST-SRM. It is proved that the
novel 5-phase switched reluctance motor under two-phase excitation
is superior among the criteria used in comparison. The purposed
model is particularly well suited for high torque and weight
constrained applications such as automobiles, aerospace and military
applications.
Abstract: This paper emphasizes on the application of genetic algorithm (GA) to optimize the parameters of the TMD for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using GA that has a story ability to find the most optimistic results. An 11–story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed GA based TMD (GATMD) controller without specifying which mode should be controlled. The results of the proposed GATMD controller are compared with the uncontrolled structure through timedomain simulation and some performance indices. The results analysis reveals that the designed GA based TMD controller has an excellent capability in reduction of the seismically excited example building and the ITAE performance, that is so for remains as unknown, can be introduced a new criteria - method for structural dynamic design.
Abstract: We present a theory for optimal filtering of infinite sets of random signals. There are several new distinctive features of the proposed approach. First, we provide a single optimal filter for processing any signal from a given infinite signal set. Second, the filter is presented in the special form of a sum with p terms where each term is represented as a combination of three operations. Each operation is a special stage of the filtering aimed at facilitating the associated numerical work. Third, an iterative scheme is implemented into the filter structure to provide an improvement in the filter performance at each step of the scheme. The final step of the concerns signal compression and decompression. This step is based on the solution of a new rank-constrained matrix approximation problem. The solution to the matrix problem is described in this paper. A rigorous error analysis is given for the new filter.
Abstract: Exponentially weighted moving average control chart (EWMA) is a popular chart used for detecting shift in the mean of parameter of distributions in quality control. The objective of this paper is to compare the efficiency of control chart to detect an increases in the mean of a process. In particular, we compared the Maximum Exponentially Weighted Moving Average (MaxEWMA) and Maximum Generally Weighted Moving Average (MaxGWMA) control charts when the observations are Exponential distribution. The criteria for evaluate the performance of control chart is called, the Average Run Length (ARL). The result of comparison show that in the case of process is small sample size, the MaxEWMA control chart is more efficiency to detect shift in the process mean than MaxGWMA control chart. For the case of large sample size, the MaxEWMA control chart is more sensitive to detect small shift in the process mean than MaxGWMA control chart, and when the process is a large shift in mean, the MaxGWMA control chart is more sensitive to detect mean shift than MaxEWMA control chart.