Abstract: Traveling salesman problem (TSP) is hard to resolve
when the number of cities and routes become large. The frequency
graph is constructed to tackle the problem. A frequency graph
maintains the topological relationships of the original weighted graph.
The numbers on the edges are the frequencies of the edges emulated
from the local optimal Hamiltonian paths. The simplest kind of local
optimal Hamiltonian paths are computed based on the four vertices
and three lines inequality. The search algorithm is given to find the
optimal Hamiltonian circuit based on the frequency graph. The
experiments show that the method can find the optimal Hamiltonian
circuit within several trials.
Abstract: The objective of positioning the fixture elements in
the fixture is to make the workpiece stiff, so that geometric errors in
the manufacturing process can be reduced. Most of the work for
optimal fixture layout used the minimization of the sum of the nodal
deflection normal to the surface as objective function. All deflections
in other direction have been neglected. We propose a new method for
fixture layout optimization in this paper, which uses the element
strain energy. The deformations in all the directions have been
considered in this way. The objective function in this method is to
minimize the sum of square of element strain energy. Strain energy
and stiffness are inversely proportional to each other. The
optimization problem is solved by the sequential quadratic
programming method. Three different kinds of case studies are
presented, and results are compared with the method using nodal
deflections as objective function to verify the propose method.
Abstract: Optimal reactive power flow is an optimization problem
with one or more objective of minimizing the active power losses for
fixed generation schedule. The control variables are generator bus
voltages, transformer tap settings and reactive power output of the
compensating devices placed on different bus bars. Biogeography-
Based Optimization (BBO) technique has been applied to solve
different kinds of optimal reactive power flow problems subject
to operational constraints like power balance constraint, line flow
and bus voltages limits etc. BBO searches for the global optimum
mainly through two steps: Migration and Mutation. In the present
work, BBO has been applied to solve the optimal reactive power
flow problems on IEEE 30-bus and standard IEEE 57-bus power
systems for minimization of active power loss. The superiority of the
proposed method has been demonstrated. Considering the quality of
the solution obtained, the proposed method seems to be a promising
one for solving these problems.
Abstract: Electromagnetic interference (EMI) is one of the
serious problems in most electrical and electronic appliances
including fluorescent lamps. The electronic ballast used to regulate
the power flow through the lamp is the major cause for EMI. The
interference is because of the high frequency switching operation of
the ballast. Formerly, some EMI mitigation techniques were in
practice, but they were not satisfactory because of the hardware
complexity in the circuit design, increased parasitic components and
power consumption and so on. The majority of the researchers have
their spotlight only on EMI mitigation without considering the other
constraints such as cost, effective operation of the equipment etc. In
this paper, we propose a technique for EMI mitigation in fluorescent
lamps by integrating Frequency Modulation and Evolutionary
Programming. By the Frequency Modulation technique, the
switching at a single central frequency is extended to a range of
frequencies, and so, the power is distributed throughout the range of
frequencies leading to EMI mitigation. But in order to meet the
operating frequency of the ballast and the operating power of the
fluorescent lamps, an optimal modulation index is necessary for
Frequency Modulation. The optimal modulation index is determined
using Evolutionary Programming. Thereby, the proposed technique
mitigates the EMI to a satisfactory level without disturbing the
operation of the fluorescent lamp.
Abstract: We study a new technique for optimal data compression
subject to conditions of causality and different types of memory. The
technique is based on the assumption that some information about
compressed data can be obtained from a solution of the associated
problem without constraints of causality and memory. This allows
us to consider two separate problem related to compression and decompression
subject to those constraints. Their solutions are given
and the analysis of the associated errors is provided.
Abstract: In this paper a procedure for the split-pipe design of looped water distribution network based on the use of simulated annealing is proposed. Simulated annealing is a heuristic-based search algorithm, motivated by an analogy of physical annealing in solids. It is capable for solving the combinatorial optimization problem. In contrast to the split-pipe design that is derived from a continuous diameter design that has been implemented in conventional optimization techniques, the split-pipe design proposed in this paper is derived from a discrete diameter design where a set of pipe diameters is chosen directly from a specified set of commercial pipes. The optimality and feasibility of the solutions are found to be guaranteed by using the proposed method. The performance of the proposed procedure is demonstrated through solving the three well-known problems of water distribution network taken from the literature. Simulated annealing provides very promising solutions and the lowest-cost solutions are found for all of these test problems. The results obtained from these applications show that simulated annealing is able to handle a combinatorial optimization problem of the least cost design of water distribution network. The technique can be considered as an alternative tool for similar areas of research. Further applications and improvements of the technique are expected as well.
Abstract: State-dependent Riccati equation based controllers are
becoming increasingly popular because of having attractive
properties like optimality, stability and robustness. This paper focuses
on the design of a roll autopilot for a fin stabilized and canard
controlled 122mm artillery rocket using state-dependent Riccati
equation technique. Initial spin is imparted to rocket during launch
and it quickly decays due to straight tail fins. After the spin phase, the
roll orientation of rocket is brought to zero with the canard deflection
commands generated by the roll autopilot. Roll autopilot has been
developed by considering uncoupled roll, pitch and yaw channels.
The canard actuator is modeled as a second-order nonlinear system.
Elements of the state weighing matrix for Riccati equation have been
chosen to be state dependent to exploit the design flexibility offered
by the Riccati equation technique. Simulation results under varying
conditions of flight demonstrate the wide operating range of the
proposed autopilot.
Abstract: A Data Warehouses is a repository of information
integrated from source data. Information stored in data warehouse is
the form of materialized in order to provide the better performance
for answering the queries. Deciding which appropriated views to be
materialized is one of important problem. In order to achieve this
requirement, the constructing search space close to optimal is a
necessary task. It will provide effective result for selecting view to be
materialized. In this paper we have proposed an approach to reoptimize
Multiple View Processing Plan (MVPP) by using global
common subexpressions. The merged queries which have query
processing cost not close to optimal would be rewritten. The
experiment shows that our approach can help to improve the total
query processing cost of MVPP and sum of query processing cost
and materialized view maintenance cost is reduced as well after views
are selected to be materialized.
Abstract: Perishable goods constitute a large portion of retailer inventory and lose value with time due to deterioration and/or obsolescence. Retailers dealing with such goods required considering the factors of short shelf life and the dependency of sales on inventory displayed in determining optimal procurement policy. Many retailers follow the practice of using two bins - primary bin sales fresh items at a list price and secondary bin sales unsold items at a discount price transferred from primary bin on attaining certain age. In this paper, mathematical models are developed for primary bin and for secondary bin that maximizes profit with decision variables of order quantities, optimal review period and optimal selling price at secondary bin. The demand rates in two bins are assumed to be deterministic and dependent on displayed inventory level, price and age but independent of each other. The validity of the model is shown by solving an example and the sensitivity analysis of the model is also reported.
Abstract: The paper presents a complete discrete statistical framework, based on a novel vector quantization (VQ) front-end process. This new VQ approach performs an optimal distribution of VQ codebook components on HMM states. This technique that we named the distributed vector quantization (DVQ) of hidden Markov models, succeeds in unifying acoustic micro-structure and phonetic macro-structure, when the estimation of HMM parameters is performed. The DVQ technique is implemented through two variants. The first variant uses the K-means algorithm (K-means- DVQ) to optimize the VQ, while the second variant exploits the benefits of the classification behavior of neural networks (NN-DVQ) for the same purpose. The proposed variants are compared with the HMM-based baseline system by experiments of specific Arabic consonants recognition. The results show that the distributed vector quantization technique increase the performance of the discrete HMM system.
Abstract: Software Reliability is one of the key factors in the software development process. Software Reliability is estimated using reliability models based on Non Homogenous Poisson Process. In most of the literature the Software Reliability is predicted only in testing phase. So it leads to wrong decision-making concept. In this paper, two Software Reliability concepts, testing and operational phase are studied in detail. Using S-Shaped Software Reliability Growth Model (SRGM) and Exponential SRGM, the testing and operational reliability values are obtained. Finally two reliability values are compared and optimal release time is investigated.
Abstract: In this paper, we present optimal control for
movement and trajectory planning for four degrees-of-freedom robot
using Fuzzy Logic (FL) and Genetic Algorithms (GAs). We have
evaluated using Fuzzy Logic (FL) and Genetic Algorithms (GAs)
for four degree-of-freedom (4 DOF) robotics arm, Uncertainties like;
Movement, Friction and Settling Time in robotic arm movement
have been compensated using Fuzzy logic and Genetic Algorithms.
The development of a fuzzy genetic optimization algorithm is
presented and discussed. The result are compared only GA and
Fuzzy GA. This paper describes genetic algorithms, which is
designed to optimize robot movement and trajectory. Though the
model represents is a general model for redundant structures and
could represent any n-link structures. The result is a complete
trajectory planning with Fuzzy logic and Genetic algorithms
demonstrating the flexibility of this technique of artificial
intelligence.
Abstract: With data centers, end-users can realize the pervasiveness of services that will be one day the cornerstone of our lives. However, data centers are often classified as computing systems that consume the most amounts of power. To circumvent such a problem, we propose a self-adaptive weighted sum methodology that jointly optimizes the performance and power consumption of any given data center. Compared to traditional methodologies for multi-objective optimization problems, the proposed self-adaptive weighted sum technique does not rely on a systematical change of weights during the optimization procedure. The proposed technique is compared with the greedy and LR heuristics for large-scale problems, and the optimal solution for small-scale problems implemented in LINDO. the experimental results revealed that the proposed selfadaptive weighted sum technique outperforms both of the heuristics and projects a competitive performance compared to the optimal solution.
Abstract: This work proposes a novel market-based air traffic flow control model considering competitive airlines in air traffic network. In the flow model, an agent based framework for resources (link/time pair) pricing is described. Resource agent and auctioneer for groups of resources are also introduced to simulate the flow management in Air Traffic Control (ATC). Secondly, the distributed group pricing algorithm is introduced, which efficiently reflect the competitive nature of the airline industry. Resources in the system are grouped according to the degree of interaction, and each auctioneer adjust s the price of one group of resources respectively until the excess demand of resources becomes zero when the demand and supply of resources of the system changes. Numerical simulation results show the feasibility of solving the air traffic flow control problem using market mechanism and pricing algorithms on the air traffic network.
Abstract: To learn about China-s future energy demand, this paper first proposed GM(1,1) model group based on recursive solutions of parameters estimation, setting up a general solving-algorithm of the model group. This method avoided the problems occurred on the past researches that remodeling, loss of information and large amount of calculation. This paper established respectively all-data-GM(1,1), metabolic GM(1,1) and new information GM (1,1)model according to the historical data of energy consumption in China in the year 2005-2010 and the added data of 2011, then modeling, simulating and comparison of accuracies we got the optimal models and to predict. Results showed that the total energy demand of China will be 37.2221 billion tons of equivalent coal in 2012 and 39.7973 billion tons of equivalent coal in 2013, which are as the same as the overall planning of energy demand in The 12th Five-Year Plan.
Abstract: Power loss reduction is one of the main targets in power industry and so in this paper, the problem of finding the optimal configuration of a radial distribution system for loss reduction is considered. Optimal reconfiguration involves the selection of the best set of branches to be opened ,one each from each loop, for reducing resistive line losses , and reliving overloads on feeders by shifting the load to adjacent feeders. However ,since there are many candidate switching combinations in the system ,the feeder reconfiguration is a complicated problem. In this paper a new approach is proposed based on a simple optimum loss calculation by determining optimal trees of the given network. From graph theory a distribution network can be represented with a graph that consists a set of nodes and branches. In fact this problem can be viewed as a problem of determining an optimal tree of the graph which simultaneously ensure radial structure of each candidate topology .In this method the refined genetic algorithm is also set up and some improvements of algorithm are made on chromosome coding. In this paper an implementation of the algorithm presented by [7] is applied by modifying in load flow program and a comparison of this method with the proposed method is employed. In [7] an algorithm is proposed that the choice of the switches to be opened is based on simple heuristic rules. This algorithm reduce the number of load flow runs and also reduce the switching combinations to a fewer number and gives the optimum solution. To demonstrate the validity of these methods computer simulations with PSAT and MATLAB programs are carried out on 33-bus test system. The results show that the performance of the proposed method is better than [7] method and also other methods.
Abstract: The use of power system stabilizers (PSSs) to damp
power system swing mode of oscillations is practical important. Our
purpose is to retune the power system stabilizer (PSS1A) parameters
in Unitrol D produced by ABB– was installed in 1995in Benghazi
North Power Plants (BNPPs) at General Electricity Company of
Libya (GECOL). The optimal values of the power system stabilizer
(PSS1A) parameters are determined off-line by a particle swarm
optimization technique (PSO). The objective is to damp the local and
inter-area modes of oscillations that occur following power system
disturbances. The retuned power system stabilizer (PSS1A) can cope
with large disturbance at different operating points and has enhanced
power system stability.
Abstract: This paper presents the results of the experimental
tests of the cooling performance of a 12,000-Btu/h modified air
conditioner (referred to as M-AC) that use the ground as a heat sink
of a condenser. In the tests, cooling capacity of M-AC with an
optimal length of a condensing coil as well as life expectancy of
copper coil buried underground were investigated. The lengths of
copper coil fabricated and used as condenser coil of M-AC were set
at 67, 50, 40 and 30 m whereas that of a 12,000-Btu/h conventional
split-type air conditioner (referred to as C-AC) was about 22 m. The
results showed that the ground can absorb heat rejected from a
condenser of M-AC. The coefficient of performance (COP) of C-AC
was about 2.5 whereas those of M-AC were found to be higher. It
was found that the values of COP of M-AC with condensing coils of
67, 50 and 40 m long were about 6.9, 5.5 and 3.3, respectively, while
that of 30-m-long one was found to be about 2.1. The electrical
consumptions of M-AC were found lower than that of C-AC in the
range of 11.5 – 15.5%. Additionally, life expectancy of underground
condensing coil of M-AC was found to be over 7 years.
Abstract: We aimed to investigate how can target and optimize
pulmonary delivery distribution by changing physicochemical
characteristics of instilled liquid.Therefore, we created a new liquids
group:
a. eligible for desired distribution within lung because of
assorted physicochemical characteristics
b. capable of being augmented with a broad range of
chemicals inertly
c. no interference on respiratory function
d. compatible with airway surface liquid
We developed forty types of new liquid,were composed of
Carboxymethylcellulose sodium,Glycerin and different types of
Polysorbates.Viscosity was measured using a Programmable
Rheometer and surface tension by KRUSS Tensiometer.We
subsequently examined the liquids and delivery protocols by simple
and branched glass capillary tube models of airways.Eventually,we
explored pulmonary distribution of liquids being augmented with
technetium-99m in mechanically ventilated rabbits.We used a single
head large field of view gamma camera.Kinematic viscosity between
0.265Stokes and 0.289Stokes,density between 1g/cm3 and 1.5g/cm3
and surface tension between 25dyn/cm and 35dyn/cm were the most
acceptable.
Abstract: For stable bipedal gait generation on the level floor,
efficient restoring of mechanical energy lost by heel collision at
the ground is necessary. Parametric excitation principle is one of
the solutions. We dealt with the robot-s total center of mass as
an inverted pendulum to consider the total dynamics of the robot.
Parametrically excited walking requires the use of continuous target
trajectory that is close to discontinuous optimal trajectory. In this
paper, we proposed the new target trajectory based on a position
in the walking direction. We surveyed relations between walking
performance and the parameters that form the target trajectory via
numerical simulations. As a result, it was found that our target
trajectory has the similar characteristics of a parametrically excited
inverted pendulum.