Abstract: Flexible Job Shop Problem (FJSP) is an extension of
classical Job Shop Problem (JSP). The FJSP extends the routing
flexibility of the JSP, i.e assigning machine to an operation. Thus it
makes it more difficult than the JSP. In this study, Cooperative Coevolutionary
Genetic Algorithm (CCGA) is presented to solve the
FJSP. Makespan (time needed to complete all jobs) is used as the
performance evaluation for CCGA. In order to test performance and
efficiency of our CCGA the benchmark problems are solved.
Computational result shows that the proposed CCGA is comparable
with other approaches.
Abstract: Encryption and decryption in RSA are done by modular exponentiation which is achieved by repeated modular multiplication. Hence efficiency of modular multiplication directly determines the efficiency of RSA cryptosystem. This paper designs a Modified Montgomery Modular Multiplication in which addition of operands is computed by 4:2 compressor. The basic logic operations in addition are partitioned over two iterations such that parallel computations are performed. This reduces the critical path delay of proposed Montgomery design. The proposed design and RSA are implemented on Virtex 2 and Virtex 5 FPGAs. The two factors partitioning and parallelism have improved the frequency and throughput of proposed design.
Abstract: The remediation of water resources pollution in
developing countries requires the application of alternative
sustainable cheaper and efficient end-of-pipe wastewater treatment
technologies. The feasibility of use of South African cheap and
abundant pine tree (Pinus patula) sawdust for development of lowcost
AC of comparable quality to expensive commercial ACs in the
abatement of water pollution was investigated. AC was developed at
optimized two-stage N2-superheated steam activation conditions in a
fixed bed reactor, and characterized for proximate and ultimate
properties, N2-BET surface area, pore size distribution, SEM, pHPZC
and FTIR. The sawdust pyrolysis activation energy was evaluated by
TGA. Results indicated that the chars prepared at 800oC and 2hrs
were suitable for development of better quality AC at 800oC and 47%
burn-off having BET surface area (1086m2/g), micropore volume
(0.26cm3/g), and mesopore volume (0.43cm3/g) comparable to
expensive commercial ACs, and suitable for water contaminants
removal. The developed AC showed basic surface functionality at
pHPZC at 10.3, and a phenol adsorption capacity that was higher than
that of commercial Norit (RO 0.8) AC. Thus, it is feasible to develop
better quality low-cost AC from (Pinus patula) sawdust using twostage
N2-steam activation in fixed-bed reactor.
Abstract: This paper presents a tested research concept that
implements a complex evolutionary algorithm, genetic algorithm
(GA), in a multi-microcontroller environment. Parallel Distributed
Genetic Algorithm (PDGA) is employed in adaptive beam forming
technique to reduce power usage of adaptive antenna at WCDMA
base station. Adaptive antenna has dynamic beam that requires more
advanced beam forming algorithm such as genetic algorithm which
requires heavy computation and memory space. Microcontrollers are
low resource platforms that are normally not associated with GAs,
which are typically resource intensive. The aim of this project was to
design a cooperative multiprocessor system by expanding the role of
small scale PIC microcontrollers to optimize WCDMA base station
transmitter power. Implementation results have shown that PDGA
multi-microcontroller system returned optimal transmitted power
compared to conventional GA.
Abstract: In this paper the design of maximally flat linear phase
finite impulse response (FIR) filters is considered. The problem is
handled with totally two different approaches. The first one is
completely deterministic numerical approach where the problem is
formulated as a Linear Complementarity Problem (LCP). The other
one is based on a combination of Markov Random Fields (MRF's)
approach with messy genetic algorithm (MGA). Markov Random
Fields (MRFs) are a class of probabilistic models that have been
applied for many years to the analysis of visual patterns or textures.
Our objective is to establish MRFs as an interesting approach to
modeling messy genetic algorithms. We establish a theoretical result
that every genetic algorithm problem can be characterized in terms of
a MRF model. This allows us to construct an explicit probabilistic
model of the MGA fitness function and introduce the Ising MGA.
Experimentations done with Ising MGA are less costly than those
done with standard MGA since much less computations are involved.
The least computations of all is for the LCP. Results of the LCP,
random search, random seeded search, MGA, and Ising MGA are
discussed.
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: Modern applications realized onto FPGAs exhibit high connectivity demands. Throughout this paper we study the routing constraints of Virtex devices and we propose a systematic methodology for designing a novel general-purpose interconnection network targeting to reconfigurable architectures. This network consists of multiple segment wires and SB patterns, appropriately selected and assigned across the device. The goal of our proposed methodology is to maximize the hardware utilization of fabricated routing resources. The derived interconnection scheme is integrated on a Virtex style FPGA. This device is characterized both for its high-performance, as well as for its low-energy requirements. Due to this, the design criterion that guides our architecture selections was the minimal Energy×Delay Product (EDP). The methodology is fully-supported by three new software tools, which belong to MEANDER Design Framework. Using a typical set of MCNC benchmarks, extensive comparison study in terms of several critical parameters proves the effectiveness of the derived interconnection network. More specifically, we achieve average Energy×Delay Product reduction by 63%, performance increase by 26%, reduction in leakage power by 21%, reduction in total energy consumption by 11%, at the expense of increase of channel width by 20%.
Abstract: In this paper, investigation of subsynchronous
resonance (SSR) characteristics of a hybrid series compensated
system and the design of voltage controller for three level 24-pulse
Voltage Source Converter based Static Synchronous Series
Compensator (SSSC) is presented. Hybrid compensation consists of
series fixed capacitor and SSSC which is a active series FACTS
controller. The design of voltage controller for SSSC is based on
damping torque analysis, and Genetic Algorithm (GA) is adopted for
tuning the controller parameters. The SSR Characteristics of SSSC
with constant reactive voltage control modes has been investigated.
The results show that the constant reactive voltage control of SSSC
has the effect of reducing the electrical resonance frequency, which
detunes the SSR.The analysis of SSR with SSSC is carried out based
on frequency domain method, eigenvalue analysis and transient
simulation. While the eigenvalue and damping torque analysis are
based on D-Q model of SSSC, the transient simulation considers both
D-Q and detailed three phase nonlinear system model using
switching functions.
Abstract: This article describes design of the 8-bit asynchronous
microcontroller simulation model in VHDL. The model is created in
ISE Foundation design tool and simulated in Modelsim tool. This
model is a simple application example of asynchronous systems
designed in synchronous design tools. The design process of creating
asynchronous system with 4-phase bundled-data protocol and with
matching delays is described in the article. The model is described in
gate-level abstraction.
The simulation waveform of the functional construction is the
result of this article. Described construction covers only the
simulation model. The next step would be creating synthesizable
model to FPGA.
Abstract: Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e., expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using genetic algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. Finally, adequacy index could be defined and used to compare some designs that have different investment costs and adequacy rates. In this paper, the proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.
Abstract: In this paper, a new Genetic Algorithm (GA) based
methodology is proposed to optimize the Degree of Hybridization
(DOH) in a passenger parallel hybrid car. At first step, target
parameters for the vehicle are decided and then using ADvanced
VehIcle SimulatOR (ADVISOR) software, the variation pattern of
these target parameters, across the different DOHs, is extracted. At
the next step, a suitable cost function is defined and is optimized
using GA. In this paper, also a new technique has been proposed for
deciding the number of battery modules for each DOH, which leads
to a great improvement in the vehicle performance. The proposed
methodology is so simple, fast and at the same time, so efficient.
Abstract: Transmission network expansion planning (TNEP) is an important component of power system planning that its task is to minimize the network construction and operational cost while satisfying the demand increasing, imposed technical and economic conditions. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, the lines adequacy rate has not been studied after the planning horizon, i.e. when the expanded network misses its adequacy and needs to be expanded again. In this paper, in order to take transmission lines condition after expansion in to account from the line loading view point, the adequacy of transmission network is considered for solution of STNEP problem. To obtain optimal network arrangement, a decimal codification genetic algorithm (DCGA) is being used for minimizing the network construction and operational cost. The effectiveness of the proposed idea is tested on the Garver's six-bus network. The results evaluation reveals that the annual worth of network adequacy has a considerable effect on the network arrangement. In addition, the obtained network, based on the DCGA, has lower investment cost and higher adequacy rate. Thus, the network satisfies the requirements of delivering electric power more safely and reliably to load centers.