A Structured Messy genetic Algorithm (SMGA) has been developed for finding the optimal way of investing a fixed budget for improvement of a water distribution network. The SMGA successfully identifies (and designs) a ...
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A Structured Messy genetic Algorithm (SMGA) has been developed for finding the optimal way of investing a fixed budget for improvement of a water distribution network. The SMGA successfully identifies (and designs) a small, near-optimal, subset of elements to be added or improved from the much larger set of all network elements.
geneticalgorithms (GAs) have been applied to the optimized design of multi-element adaptive antenna arrays and both passive and active wideband radar absorbers, particularly for the case of an end-fire antenna with b...
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geneticalgorithms (GAs) have been applied to the optimized design of multi-element adaptive antenna arrays and both passive and active wideband radar absorbers, particularly for the case of an end-fire antenna with both adaptive nulling and radiation pattern envelope limitations applied. The algorithms were robust and outperformed other optimization techniques such as down hill simplex and simulated annealing.
Many engineering problems may be described as a search for one near optimal description amongst many possibilities, given certain constraints. Search techniques, such as genetic programming, seem appropriate to repres...
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Many engineering problems may be described as a search for one near optimal description amongst many possibilities, given certain constraints. Search techniques, such as genetic programming, seem appropriate to represent many problems. This paper describes a grammatically based learning technique, based upon the genetic programming paradigm, that allows declarative biasing and modifies the bias as the evolution proceeds. The use of bias allows complex problems to be represented and searched efficiently.
In this paper an improvement of a genetic algorithm using in constructing an IIR digital filter is presented. The aim of our improvement are reconstruction of genetic operators and new procedure for initial population...
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In this paper an improvement of a genetic algorithm using in constructing an IIR digital filter is presented. The aim of our improvement are reconstruction of genetic operators and new procedure for initial population selecting applied on a filter design problem. The result of the paper is modified genetic algorithm which allow us to find the best IIR filter among all filters with a required transfer function. The best one is the one with minimal phase and minimum group delay.
A system has been developed for the design of building heating systems. It makes use of a computer language called MDL (Model Description Language) which includes provisions for the specification of restraints and cos...
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A system has been developed for the design of building heating systems. It makes use of a computer language called MDL (Model Description Language) which includes provisions for the specification of restraints and cost functions, and a simulation and genetic algorithm software called QUEST. One shortcoming of the system is the relatively long length of time for optimization results to be obtained. The efficiency of the simulator could be improved through hardware parallelization. Although the system was originally intended for the evaluation, simulation, and optimization of building heating systems, the use of bond graph methodology has widened the scope to include a much wider range of dynamic systems.
This paper deals with the problem of determining optimally the levels of stocks and the quantities of production and transportation in an integrated production-inventory-distribution system. An integer program is deve...
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This paper deals with the problem of determining optimally the levels of stocks and the quantities of production and transportation in an integrated production-inventory-distribution system. An integer program is developed to minimize the total cost in the system. A genetic search algorithm is formulated to solve this problem. A numerical example is employed to illustrate the effectiveness of the algorithm.
This paper presents a method of designing Proportional-Integral-Differential (PID) controllers for single-input, single-output (SISO) systems. We used a genetic Algorithm implemented in hardware for setting the K valu...
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This paper presents a method of designing Proportional-Integral-Differential (PID) controllers for single-input, single-output (SISO) systems. We used a genetic Algorithm implemented in hardware for setting the K values of the PID controller and minimizing the integral error in the system. The system have been applied to a PID controller system with variable plant transfer function. The method has been successfully tested and some results are presented.
This paper discusses the application of geneticalgorithms (GAs) to the problem of searching for a set of synchronization codes for TDMA based mobile radio systems. The problem may be formulated as a constrained optim...
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This paper discusses the application of geneticalgorithms (GAs) to the problem of searching for a set of synchronization codes for TDMA based mobile radio systems. The problem may be formulated as a constrained optimization problem and is transformed into an unconstrained one by including a penalty term within the fitness function. The quality of the sequences obtained, using the geneticalgorithms, are compared with some previously published results. The paper discusses the sensitivity of the genetic algorithm's behaviour to the formulation of the fitness function and algorithm parameters. Using results from polyphase codes it is also shown how sets of sequences for different modulation formats can be obtained from either a BPSK or QPSK code.
A genetic algorithm for the physical design of VLSI-chips is presented. The algorithm simultaneously optimizes the placement of the cells with the total routing. During the placement the detailed routing is done, whil...
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A genetic algorithm for the physical design of VLSI-chips is presented. The algorithm simultaneously optimizes the placement of the cells with the total routing. During the placement the detailed routing is done, while the global routes are optimized by the genetic algorithm. This is just opposed to the usual serial approach, where the computation of the detailed routing is the last step in the layout-design.
The technique of geneticalgorithms is proposed as a means of auto-tuning PID controllers. The technique revolves firstly using on-line data and the genetic algorithm to identify a model of the process. Then the ident...
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The technique of geneticalgorithms is proposed as a means of auto-tuning PID controllers. The technique revolves firstly using on-line data and the genetic algorithm to identify a model of the process. Then the identified model, the genetic algorithm and simulation methods, are used to off-line tune the PID controller, so as to minimize a time-domain based cost function. Finally, the genetically tuned controller is implemented on-line on the real process. The results of the genetic auto-tuner are illustrated by auto-tuning a PID controller on a laboratory heat exchanger, and comparing the genetic auto-tuning technique with the Astrom-relay auto-tuning technique.
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