Abstract: This paper proposes an application of the differential
evolution (DE) algorithm for solving the economic dispatch problem
(ED). Furthermore, the regenerating population procedure added to
the conventional DE in order to improve escaping the local minimum
solution. To test performance of DE algorithm, three thermal
generating units with valve-point loading effects is used for testing.
Moreover, investigating the DE parameters is presented. The
simulation results show that the DE algorithm, which had been
adjusted parameters, is better convergent time than other optimization
methods.
Abstract: This research presents the development of simulation
modeling for WIP management in semiconductor fabrication.
Manufacturing simulation modeling is needed for productivity
optimization analysis due to the complex process flows involved
more than 35 percent re-entrance processing steps more than 15 times
at same equipment. Furthermore, semiconductor fabrication required
to produce high product mixed with total processing steps varies from
300 to 800 steps and cycle time between 30 to 70 days. Besides the
complexity, expansive wafer cost that potentially impact the
company profits margin once miss due date is another motivation to
explore options to experiment any analysis using simulation
modeling. In this paper, the simulation model is developed using
existing commercial software platform AutoSched AP, with
customized integration with Manufacturing Execution Systems
(MES) and Advanced Productivity Family (APF) for data collections
used to configure the model parameters and data source. Model
parameters such as processing steps cycle time, equipment
performance, handling time, efficiency of operator are collected
through this customization. Once the parameters are validated, few
customizations are made to ensure the prior model is executed. The
accuracy for the simulation model is validated with the actual output
per day for all equipments. The comparison analysis from result of
the simulation model compared to actual for achieved 95 percent
accuracy for 30 days. This model later was used to perform various
what if analysis to understand impacts on cycle time and overall
output. By using this simulation model, complex manufacturing
environment like semiconductor fabrication (fab) now have
alternative source of validation for any new requirements impact
analysis.
Abstract: The after–sales activities are nowadays acknowledged
as a relevant source of revenue, profit and competitive advantage in
most manufacturing industries. Top and middle management,
therefore, should focus on the definition of a structured business
performance measurement system for the after-sales business. The
paper aims at filling this gap, and presents an integrated methodology
for the after-sales network performance measurement, and provides
an empirical application to automotive case companies and their
official service network. This is the first study that presents an
integrated multivariate approach for total assessment and
improvement of after-sale services.
Abstract: Ant colony optimization (ACO) and its variants are
applied extensively to resolve various continuous optimization
problems. As per the various diversification and intensification
schemes of ACO for continuous function optimization, researchers
generally consider components of multidimensional state space to
generate the new search point(s). However, diversifying to a new
search space by updating only components of the multidimensional
vector may not ensure that the new point is at a significant distance
from the current solution. If a minimum distance is not ensured
during diversification, then there is always a possibility that the
search will end up with reaching only local optimum. Therefore, to
overcome such situations, a Mahalanobis distance-based
diversification with Nelder-Mead simplex-based search scheme for
each ant is proposed for the ACO strategy. A comparative
computational run results, based on nine nonlinear standard test
problems, confirms that the performance of ACO is improved
significantly with the integration of the proposed schemes in the
ACO.
Abstract: This paper reports the study results on neural network
training algorithm of numerical optimization techniques multiface
detection in static images. The training algorithms involved are scale
gradient conjugate backpropagation, conjugate gradient
backpropagation with Polak-Riebre updates, conjugate gradient
backpropagation with Fletcher-Reeves updates, one secant
backpropagation and resilent backpropagation. The final result of
each training algorithms for multiface detection application will also
be discussed and compared.
Abstract: Usually, the solid-fuel flow of an iron ore sinter plant
consists of different types of the solid-fuels, which differ from each
other. Information about the composition of the solid-fuel flow
usually comes every 8-24 hours. It can be clearly seen that this
information cannot be used to control the sintering process in real
time. Due to this, we propose an expert system which uses indirect
measurements from the process in order to obtain the composition of
the solid-fuel flow by solving an optimization task. Then this
information can be used to control the sintering process. The
proposed technique can be successfully used to improve sinter
quality and reduce the amount of solid-fuel used by the process.
Abstract: Many real-world optimization problems involve multiple conflicting objectives and the use of evolutionary algorithms to solve the problems has attracted much attention recently. This paper investigates the application of multi-objective optimization technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the performance of a power system. The design objective is to improve both rotor angle stability and system voltage profile. A Genetic Algorithm (GA) based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimisation problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented to show the effectiveness and robustness of the proposed approach.
Abstract: Today, Genetic Algorithm has been used to solve
wide range of optimization problems. Some researches conduct on
applying Genetic Algorithm to text classification, summarization
and information retrieval system in text mining process. This
researches show a better performance due to the nature of Genetic
Algorithm. In this paper a new algorithm for using Genetic
Algorithm in concept weighting and topic identification, based on
concept standard deviation will be explored.
Abstract: Optimization of cutting parameters important in precision machining in regards to efficiency and surface integrity of the machined part. Usually productivity and precision in machining is limited by the forces emanating from the cutting process. Due to the inherent varying nature of the workpiece in terms of geometry and material composition, the peak cutting forces vary from point to point during machining process. In order to increase productivity without compromising on machining accuracy, it is important to control these cutting forces. In this paper a fuzzy logic control algorithm is developed that can be applied in the control of peak cutting forces in milling of spherical surfaces using ball end mills. The controller can adaptively vary the feedrate to maintain allowable cutting force on the tool. This control algorithm is implemented in a computer numerical control (CNC) machine. It has been demonstrated that the controller can provide stable machining and improve the performance of the CNC milling process by varying feedrate.
Abstract: Shadows add great amount of realism to a scene and
many algorithms exists to generate shadows. Recently, Shadow
volumes (SVs) have made great achievements to place a valuable
position in the gaming industries. Looking at this, we concentrate on
simple but valuable initial partial steps for further optimization in SV
generation, i.e.; model simplification and silhouette edge detection
and tracking. Shadow volumes (SVs) usually takes time in generating
boundary silhouettes of the object and if the object is complex then
the generation of edges become much harder and slower in process.
The challenge gets stiffer when real time shadow generation and
rendering is demanded. We investigated a way to use the real time
silhouette edge detection method, which takes the advantage of
spatial and temporal coherence, and exploit the level-of-details
(LOD) technique for reducing silhouette edges of the model to use
the simplified version of the model for shadow generation speeding
up the running time. These steps highly reduce the execution time of
shadow volume generations in real-time and are easily flexible to any
of the recently proposed SV techniques. Our main focus is to exploit
the LOD and silhouette edge detection technique, adopting them to
further enhance the shadow volume generations for real time
rendering.
Abstract: There are a number of different cars for transferring hundreds of close contacts of swine influenza patients to hospital, and we need to carefully assign the passengers to those cars in order to minimize the risk of influenza spreading during transportation. The paper presents an approach to straightforward obtain the optimal solution of the relaxed problems, and develops two iterative improvement algorithms to effectively tackle the general problem.
Abstract: The overall objective of this research is a strain
improvement technology for efficient pectinase production. A novel
cells cultivation technology by immobilization of fungal cells has
been studied in long time continuous fermentations. Immobilization
was achieved by using of new material for absorption of stores of
immobilized cultures which was for the first time used for
immobilization of microorganisms. Effects of various conditions of
nitrogen and carbon nutrition on the biosynthesis of pectolytic
enzymes in Aspergillus awamori 1-8 strain were studied. Proposed
cultivation technology along with optimization of media components
for pectinase overproduction led to increased pectinase productivity
in Aspergillus awamori 1-8 from 7 to 8 times. Proposed technology
can be applied successfully for production of major industrial
enzymes such as α-amylase, protease, collagenase etc.
Abstract: Starting from a biologically inspired framework, Gabor filters were built up from retinal filters via LMSE algorithms. Asubset of retinal filter kernels was chosen to form a particular Gabor filter by using a weighted sum. One-dimensional optimization approaches were shown to be inappropriate for the problem. All model parameters were fixed with biological or image processing constraints. Detailed analysis of the optimization procedure led to the introduction of a minimization constraint. Finally, quantization of weighting factors was investigated. This resulted in an optimized cascaded structure of a Gabor filter bank implementation with lower computational cost.
Abstract: Bioleaching of spent catalyst using moderate thermophilic chemolithotrophic acidophiles in growth medium without Fe source was investigated with two different pulp densities and three different size fractions. All the experiments were conducted on shake flasks at a temperature of 65 °C. The leaching yield of Ni and Al was found to be promising with very high leaching yield of 92-96% followed by Al as 41-76%, which means both Ni and Al leaching were favored by the moderate thermophilic bioleaching compared to the mesophilic bioleaching. The acid consumption was comparatively higher for the 10% pulp density experiments. Comparatively minimal difference in the leaching yield with different size fractions and different pulp densities show no requirement of grinding and using low pulp density less than 10%. This process would rather be economical as well as eco-friendly process for future optimization of the recovery of metal values from spent catalyst.
Abstract: This paper presents a study of the Taguchi design
application to optimize surface quality in damper inserted end milling
operation. Maintaining good surface quality usually involves
additional manufacturing cost or loss of productivity. The Taguchi
design is an efficient and effective experimental method in which a
response variable can be optimized, given various factors, using
fewer resources than a factorial design. This Study included spindle
speed, feed rate, and depth of cut as control factors, usage of different
tools in the same specification, which introduced tool condition and
dimensional variability. An orthogonal array of L9(3^4)was used;
ANOVA analyses were carried out to identify the significant factors
affecting surface roughness, and the optimal cutting combination was
determined by seeking the best surface roughness (response) and
signal-to-noise ratio. Finally, confirmation tests verified that the
Taguchi design was successful in optimizing milling parameters for
surface roughness.
Abstract: In this paper we develop an efficient numerical method for the finite-element model updating of damped gyroscopic systems based on incomplete complex modal measured data. It is assumed that the analytical mass and stiffness matrices are correct and only the damping and gyroscopic matrices need to be updated. By solving a constrained optimization problem, the optimal corrected symmetric damping matrix and skew-symmetric gyroscopic matrix complied with the required eigenvalue equation are found under a weighted Frobenius norm sense.
Abstract: This paper presents the solution of power economic dispatch (PED) problem of generating units with valve point effects and multiple fuel options using Self-Adaptive Differential Evolution (SDE) algorithm. The global optimal solution by mathematical approaches becomes difficult for the realistic PED problem in power systems. The Differential Evolution (DE) algorithm is found to be a powerful evolutionary algorithm for global optimization in many real problems. In this paper the key parameters of control in DE algorithm such as the crossover constant CR and weight applied to random differential F are self-adapted. The PED problem formulation takes into consideration of nonsmooth fuel cost function due to valve point effects and multi fuel options of generator. The proposed approach has been examined and tested with the numerical results of PED problems with thirteen-generation units including valve-point effects, ten-generation units with multiple fuel options neglecting valve-point effects and ten-generation units including valve-point effects and multiple fuel options. The test results are promising and show the effectiveness of proposed approach for solving PED problems.
Abstract: In this paper a mixed method by combining an evolutionary and a conventional technique is proposed for reduction of Single Input Single Output (SISO) continuous systems into Reduced Order Model (ROM). In the conventional technique, the mixed advantages of Mihailov stability criterion and continued Fraction Expansions (CFE) technique is employed where the reduced denominator polynomial is derived using Mihailov stability criterion and the numerator is obtained by matching the quotients of the Cauer second form of Continued fraction expansions. Then, retaining the numerator polynomial, the denominator polynomial is recalculated by an evolutionary technique. In the evolutionary method, the recently proposed Differential Evolution (DE) optimization technique is employed. DE method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. The proposed method is illustrated through a numerical example and compared with ROM where both numerator and denominator polynomials are obtained by conventional method to show its superiority.
Abstract: Rambutan is a tropical fruit which peel possesses antioxidant properties. This work was conducted to optimize extraction conditions of phenolic compounds from rambutan peel. Response surface methodology (RSM) was adopted to optimize subcritical water extraction (SWE) on temperature, extraction time and percent solvent mixture. The results demonstrated that the optimum conditions for SWE were as follows: temperature 160°C, extraction time 20min. and concentration of 50% ethanol. Comparison of the phenolic compounds from the rambutan peels in maceration 6h, soxhlet 4h, and SWE 20min., it indicated that total phenolic content (using Folin-Ciocalteu-s phenol reagent) was 26.42, 70.29, and 172.47mg of tannic acid equivalent (TAE) per g dry rambutan peel, respectively. The comparative study concluded that SWE was a promising technique for phenolic compounds extraction from rambutan peel, due to much more two times of conventional techniques and shorter extraction times.
Abstract: The study of proteomics reached unexpected levels of
interest, as a direct consequence of its discovered influence over
some complex biological phenomena, such as problematic diseases
like cancer. This paper presents a new technique that allows for an
accurate analysis of the human interactome network. It is basically
a two-step analysis process that involves, at first, the detection of
each protein-s absolute importance through the betweenness centrality
computation. Then, the second step determines the functionallyrelated
communities of proteins. For this purpose, we use a community
detection technique that is based on the edge betweenness
calculation. The new technique was thoroughly tested on real biological
data and the results prove some interesting properties of those proteins that are involved in the carcinogenesis process. Apart from its
experimental usefulness, the novel technique is also computationally
effective in terms of execution times. Based on the analysis- results, some topological features of cancer mutated proteins are presented
and a possible optimization solution for cancer drugs design is suggested.