Abstract: Due to the deregulation of the Electric Supply
Industry and the resulting emergence of electricity market, the
volumes of power purchases are on the rise all over the world. In a
bid to meet the customer-s demand in a reliable and yet economic
manner, utilities purchase power from the energy market over and
above its own production. This paper aims at developing an optimal
power purchase model with two objectives viz economy and
environment ,taking various functional operating constraints such as
branch flow limits, load bus voltage magnitudes limits, unit capacity
constraints and security constraints into consideration.The price of
purchased power being an uncertain variable is modeled using fuzzy
logic. DEMO (Differential Evolution For Multi-objective
Optimization) is used to obtain the pareto-optimal solution set of the
multi-objective problem formulated. Fuzzy set theory has been
employed to extract the best compromise non-dominated solution.
The results obtained on IEEE 30 bus system are presented and
compared with that of NSGAII.
Abstract: In this paper newly reported Cosh window function is
used in the design of prototype filter for M-channel Near Perfect
Reconstruction (NPR) Cosine Modulated Filter Bank (CMFB). Local
search optimization algorithm is used for minimization of distortion
parameters by optimizing the filter coefficients of prototype filter.
Design examples are presented and comparison has been made with
Kaiser window based filterbank design of recently reported work.
The result shows that the proposed design approach provides lower
distortion parameters and improved far-end suppression than the
Kaiser window based design of recent reported work.
Abstract: Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.
Abstract: This work concerns the topological optimization
problem for determining the optimal petroleum refinery
configuration. We are interested in further investigating and
hopefully advancing the existing optimization approaches and
strategies employing logic propositions to conceptual process
synthesis problems. In particular, we seek to contribute to this
increasingly exciting area of chemical process modeling by
addressing the following potentially important issues: (a) how the
formulation of design specifications in a mixed-logical-and-integer
optimization model can be employed in a synthesis problem to enrich
the problem representation by incorporating past design experience,
engineering knowledge, and heuristics; and (b) how structural
specifications on the interconnectivity relationships by space (states)
and by function (tasks) in a superstructure should be properly
formulated within a mixed-integer linear programming (MILP)
model. The proposed modeling technique is illustrated on a case
study involving the alternative processing routes of naphtha, in which
significant improvement in the solution quality is obtained.
Abstract: Weather systems use enormously complex
combinations of numerical tools for study and forecasting.
Unfortunately, due to phenomena in the world climate, such
as the greenhouse effect, classical models may become
insufficient mostly because they lack adaptation. Therefore,
the weather forecast problem is matched for heuristic
approaches, such as Evolutionary Algorithms.
Experimentation with heuristic methods like Particle Swarm
Optimization (PSO) algorithm can lead to the development of
new insights or promising models that can be fine tuned with
more focused techniques. This paper describes a PSO
approach for analysis and prediction of data and provides
experimental results of the aforementioned method on realworld
meteorological time series.
Abstract: The increasing competitiveness in manufacturing
industry is forcing manufacturers to seek effective processing
schedules. The paper presents an optimization manufacture
scheduling approach for dependent details processing with given
processing sequences and times on multiple machines. By defining
decision variables as start and end moments of details processing it is
possible to use straightforward variables restrictions to satisfy
different technological requirements and to formulate easy to
understand and solve optimization tasks for multiple numbers of
details and machines. A case study example is solved for seven base
moldings for CNC metalworking machines processed on five
different machines with given processing order among details and
machines and known processing time-s duration. As a result of linear
optimization task solution the optimal manufacturing schedule
minimizing the overall processing time is obtained. The
manufacturing schedule defines the moments of moldings delivery
thus minimizing storage costs and provides mounting due-time
satisfaction. The proposed optimization approach is based on real
manufacturing plant problem. Different processing schedules variants
for different technological restrictions were defined and implemented
in the practice of Bulgarian company RAIS Ltd. The proposed
approach could be generalized for other job shop scheduling
problems for different applications.
Abstract: In this paper, an artificial intelligent technique for
robust digital image watermarking in multiwavelet domain is
proposed. The embedding technique is based on the quantization
index modulation technique and the watermark extraction process
does not require the original image. We have developed an
optimization technique using the genetic algorithms to search for
optimal quantization steps to improve the quality of watermarked
image and robustness of the watermark. In addition, we construct a
prediction model based on image moments and back propagation
neural network to correct an attacked image geometrically before the
watermark extraction process begins. The experimental results show
that the proposed watermarking algorithm yields watermarked image
with good imperceptibility and very robust watermark against various
image processing attacks.
Abstract: As global industry developed rapidly, the energy
demand also rises simultaneously. In the production process, there’s a
lot of energy consumed in the process. Formally, the energy used in
generating the heat in the production process. In the total energy
consumption, 40% of the heat was used in process heat, mechanical
work, chemical energy and electricity. The remaining 50% were
released into the environment. It will cause energy waste and
environment pollution. There are many ways for recovering the waste
heat in factory. Organic Rankine Cycle (ORC) system can produce
electricity and reduce energy costs by recovering the waste of low
temperature heat in the factory. In addition, ORC is the technology
with the highest power generating efficiency in low-temperature heat
recycling. However, most of factories executives are still hesitated
because of the high implementation cost of the ORC system, even a lot
of heat are wasted. Therefore, this study constructs a nonlinear
mathematical model of waste heat recovery equipment configuration
to maximize profits. A particle swarm optimization algorithm is
developed to generate the optimal facility installation plan for the ORC
system.
Abstract: The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.
Abstract: Seismic design may require non-conventional
concept, due to the fact that the stiffness and layout of the structure
have a great effect on the overall structural behaviour, on the seismic
load intensity as well as on the internal force distribution. To find an
economical and optimal structural configuration the key issue is the
optimal design of the lateral load resisting system. This paper focuses
on the optimal design of regular, concentric braced frame (CBF)
multi-storey steel building structures. The optimal configurations are
determined by a numerical method using genetic algorithm approach,
developed by the authors. Aim is to find structural configurations
with minimum structural cost. The design constraints of objective
function are assigned in accordance with Eurocode 3 and Eurocode 8
guidelines. In this paper the results are presented for various building
geometries, different seismic intensities, and levels of energy
dissipation.
Abstract: This paper proposes the concept of aerocapture with
aerodynamic-environment-adaptive variable geometry flexible
aeroshell that vehicle deploys. The flexible membrane is composed
of thin-layer film or textile as its aeroshell in order to solve some
problems obstructing realization of aerocapture technique.
Multi-objective optimization study is conducted to investigate
solutions and derive design guidelines. As a result, solutions which
can avoid aerodynamic heating and enlarge the corridor width up
to 10% are obtained successfully, so that the effectiveness of this
concept can be demonstrated. The deformation-use optimum
solution changes its drag coefficient from 1.6 to 1.1, along with the
change in dynamic pressure. Moreover, optimization results show
that deformation-use solution requires the membrane for which
upper temperature limit and strain limit are more than 700 K and
120%, respectively, and elasticity (Young-s modulus) is of order of
106 Pa.
Abstract: In this paper, we consider the effect of the initial
sample size on the performance of a sequential approach that used
in selecting a good enough simulated system, when the number
of alternatives is very large. We implement a sequential approach
on M=M=1 queuing system under some parameter settings, with a
different choice of the initial sample sizes to explore the impacts on
the performance of this approach. The results show that the choice
of the initial sample size does affect the performance of our selection
approach.
Abstract: A manufacturing inventory model with shortages with
carrying cost, shortage cost, setup cost and demand quantity as
imprecise numbers, instead of real numbers, namely interval number
is considered here. First, a brief survey of the existing works on
comparing and ranking any two interval numbers on the real line
is presented. A common algorithm for the optimum production
quantity (Economic lot-size) per cycle of a single product (so as
to minimize the total average cost) is developed which works well
on interval number optimization under consideration. Finally, the
designed algorithm is illustrated with numerical example.
Abstract: Studies on Simultaneous Saccharification and Fermentation (SSF) of corn flour, a major agricultural product as the substrate using starch digesting glucoamylase enzyme derived from Aspergillus niger and non starch digesting and sugar fermenting Saccharomyces cerevisiae in a batch fermentation. Experiments based on Central Composite Design (CCD) were conducted to study the effect of substrate concentration, pH, temperature, enzyme concentration on Ethanol Concentration and the above parameters were optimized using Response Surface Methodology (RSM). The optimum values of substrate concentration, pH, temperature and enzyme concentration were found to be 160 g/l, 5.5, 30°C and 50 IU respectively. The effect of inoculums age on ethanol concentration was also investigated. The corn flour solution equivalent to 16% initial starch concentration gave the highest ethanol concentration of 63.04 g/l after 48 h of fermentation at optimum conditions of pH and temperature. Monod model and Logistic model were used for growth kinetics and Leudeking – Piret model was used for product formation kinetics.
Abstract: The data exchanged on the Web are of different nature
from those treated by the classical database management systems;
these data are called semi-structured data since they do not have a
regular and static structure like data found in a relational database;
their schema is dynamic and may contain missing data or types.
Therefore, the needs for developing further techniques and
algorithms to exploit and integrate such data, and extract relevant
information for the user have been raised. In this paper we present
the system OSIX (Osiris based System for Integration of XML
Sources). This system has a Data Warehouse model designed for the
integration of semi-structured data and more precisely for the
integration of XML documents. The architecture of OSIX relies on
the Osiris system, a DL-based model designed for the representation
and management of databases and knowledge bases. Osiris is a viewbased
data model whose indexing system supports semantic query
optimization. We show that the problem of query processing on a
XML source is optimized by the indexing approach proposed by
Osiris.
Abstract: The vehicle routing problem (VRP) is a famous combinatorial optimization problem. Because of its well-known difficulty, metaheuristics are the most appropriate methods to tackle large and realistic instances. The goal of this paper is to highlight the key ideas for designing VRP metaheuristics according to the following criteria: efficiency, speed, robustness, and ability to take advantage of the problem structure. Such elements can obviously be used to build solution methods for other combinatorial optimization problems, at least in the deterministic field.
Abstract: This article presents the simulation, parameterization and optimization of an electromagnet with the C–shaped configuration, intended for the study of magnetic properties of materials. The electromagnet studied consists of a C-shaped yoke, which provides self–shielding for minimizing losses of magnetic flux density, two poles of high magnetic permeability and power coils wound on the poles. The main physical variable studied was the static magnetic flux density in a column within the gap between the poles, with 4cm2 of square cross section and a length of 5cm, seeking a suitable set of parameters that allow us to achieve a uniform magnetic flux density of 1x104 Gaussor values above this in the column, when the system operates at room temperature and with a current consumption not exceeding 5A. By means of a magnetostatic analysis by the finite element method, the magnetic flux density and the distribution of the magnetic field lines were visualized and quantified. From the results obtained by simulating an initial configuration of electromagnet, a structural optimization of the geometry of the adjustable caps for the ends of the poles was performed. The magnetic permeability effect of the soft magnetic materials used in the poles system, such as low– carbon steel (0.08% C), Permalloy (45% Ni, 54.7% Fe) and Mumetal (21.2% Fe, 78.5% Ni), was also evaluated. The intensity and uniformity of the magnetic field in the gap showed a high dependence with the factors described above. The magnetic field achieved in the column was uniform and its magnitude ranged between 1.5x104 Gauss and 1.9x104 Gauss according to the material of the pole used, with the possibility of increasing the magnetic field by choosing a suitable geometry of the cap, introducing a cooling system for the coils and adjusting the spacing between the poles. This makes the device a versatile and scalable tool to generate the magnetic field necessary to perform magnetic characterization of materials by techniques such as vibrating sample magnetometry (VSM), Hall-effect, Kerr-effect magnetometry, among others. Additionally, a CAD design of the modules of the electromagnet is presented in order to facilitate the construction and scaling of the physical device.
Abstract: This paper presents modeling and optimization of two NP-hard problems in flexible manufacturing system (FMS), part type selection problem and loading problem. Due to the complexity and extent of the problems, the paper was split into two parts. The first part of the papers has discussed the modeling of the problems and showed how the real coded genetic algorithms (RCGA) can be applied to solve the problems. This second part discusses the effectiveness of the RCGA which uses an array of real numbers as chromosome representation. The novel proposed chromosome representation produces only feasible solutions which minimize a computational time needed by GA to push its population toward feasible search space or repair infeasible chromosomes. The proposed RCGA improves the FMS performance by considering two objectives, maximizing system throughput and maintaining the balance of the system (minimizing system unbalance). The resulted objective values are compared to the optimum values produced by branch-and-bound method. The experiments show that the proposed RCGA could reach near optimum solutions in a reasonable amount of time.
Abstract: Smart Dust particles, are small smart materials used for generating weather maps. We investigate question of the optimal number of Smart Dust particles necessary for generating precise, computationally feasible and cost effective 3–D weather maps. We also give an optimal matching algorithm for the generalized scenario, when there are N Smart Dust particles and M ground receivers.
Abstract: In the past years, the world has witnessed significant work in the field of Manufacturing. Special efforts have been made in the implementation of new technologies, management and control systems, among many others which have all evolved the field. Closely following all this, due to the scope of new projects and the need of turning the existing flexible ideas into more autonomous and intelligent ones, i.e.: moving toward a more intelligent manufacturing, the present paper emerges with the main aim of contributing to the analysis and a few customization issues of a new iCIM 3000 system at the IPSAM. In this process, special emphasis in made on the material flow problem. For this, besides offering a description and analysis of the system and its main parts, also some tips on how to define other possible alternative material flow scenarios and a partial analysis of the combinatorial nature of the problem are offered as well. All this is done with the intentions of relating it with the use of simulation tools, for which these have been briefly addressed with a special focus on the Witness simulation package. For a better comprehension, the previous elements are supported by a few figures and expressions which would help obtaining necessary data. Such data and others will be used in the future, when simulating the scenarios in the search of the best material flow configurations.