Evolutionary divide and conquer (EDAC) applied to the geometric travelling salesman problem uses a genetic algorithm to explore the space of problem subdivisions. The underlying techniques for subdivision and patching...
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Evolutionary divide and conquer (EDAC) applied to the geometric travelling salesman problem uses a genetic algorithm to explore the space of problem subdivisions. The underlying techniques for subdivision and patching are based on the cellular dissection algorithms of Richard Karp, but the addition of new repair heuristics as well as the genetic algorithm, appears to have succeeded in lifting the quality of solution way above Karp's algorithms, whist maintaining almost linear scaling of the algorithm with increased problem size. In this paper we outline a parallel implementation of EDAC and present some preliminary results of this work.
We describe the application of a hardware genetic algorithm processor to handle the economic power dispatch problem. We have analyzed a variety of configurations including varying the string word length and the introd...
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We describe the application of a hardware genetic algorithm processor to handle the economic power dispatch problem. We have analyzed a variety of configurations including varying the string word length and the introduction of multiple processor configurations. Results show that multiple genetic algorithm processor configurations work better than other configurations with less complexity. It is possible to apply multiple configurations to larger numbers of generators in the problem.
In this paper, a novel technique for matching images of object shapes which have been subject to affine transformation caused by variations in the camera position is reported. The method is based on the genetic Algori...
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In this paper, a novel technique for matching images of object shapes which have been subject to affine transformation caused by variations in the camera position is reported. The method is based on the genetic Algorithm, and is more efficient and reliable than conventional approaches that rely on dominant points to determine the best alignment between object boundaries. Experimental results are reported which demonstrate the feasibility of the approach and its potential in practical applications.
geneticalgorithms (GAs) offer a more attractive option for the optimization of combinational and sequential logic, namely: the minimization of fixed polarity Reed-Muller (RM) expansions, the minimization of exclusive...
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geneticalgorithms (GAs) offer a more attractive option for the optimization of combinational and sequential logic, namely: the minimization of fixed polarity Reed-Muller (RM) expansions, the minimization of exclusive-OR sum-of-products (ESOP) expansions, and the determination of optimal state assignments for finite or algorithmic state machines (FSMs and ASMs). The GAs are not limited to producing the same results for the optimization problems;the designer may, if desired, allow the GAs to develop greater numbers of generation, thus increasing the scope of the search. The effectiveness of the method may be improved further with emerging techniques such as alternative parent selection and crossover mechanisms.
The frequency assignment problem, known to be NP-complete, is to find an assignment of radio frequencies to a set of transmitters in a region. The transmitters satisfy a large number of constraints. This paper present...
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The frequency assignment problem, known to be NP-complete, is to find an assignment of radio frequencies to a set of transmitters in a region. The transmitters satisfy a large number of constraints. This paper presents a simulated annealing algorithm for determining such an assignment and compares the results with those obtained from a genetic algorithm. We report on our computational experiments in terms of quality of the solutions obtained for realistic, computer-generated problem instances.
This paper describes an attempt to enable computers to generate truly novel conceptual designs of solid objects by using geneticalgorithms (GAs). The current capabilities of the system are illustrated by the example ...
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This paper describes an attempt to enable computers to generate truly novel conceptual designs of solid objects by using geneticalgorithms (GAs). The current capabilities of the system are illustrated by the example of designing a table. Each individual table has its functionality specified by an explicit objective function, which is utilized by GAs to evolve candidate designs. These designs are represented using spatial partitions of `stretched cubes'. The effect that varying the number of spatial partitions in each design has on evolution is investigated. Additionally, a method of producing symmetrical designs is explored.
geneticalgorithms have been widely applied to optimization problems for which existing approaches are computationally too expensive. This paper presents a genetic algorithm for finding a constrained minimum spanning ...
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geneticalgorithms have been widely applied to optimization problems for which existing approaches are computationally too expensive. This paper presents a genetic algorithm for finding a constrained minimum spanning tree. The problem is of relevance in the design of minimum cost communication networks, where there is a need to connect all the terminals at a user site to a terminal concentrator in a multipoint (tree) configuration, while ensuring that link capacity constraints are not violated. Test results show that the solutions from the proposed algorithm are broadly comparable with, and in several cases, better than, those obtained from traditional heuristic methods, such as the Prim and Esau-Williams algorithms.
A genetic Algorithm (GA) has been applied to optimize target pressure distributions for aerodynamic inverse design methods. Since GAs do not require any derivative information, the resulting aerodynamic optimization a...
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A genetic Algorithm (GA) has been applied to optimize target pressure distributions for aerodynamic inverse design methods. Since GAs do not require any derivative information, the resulting aerodynamic optimization algorithm is robust. Once target pressure distributions are obtained, corresponding airfoil geometries can be computed by an inverse design code using a Navier-Stokes solver. Design samples indicate that supercritical airfoil shapes are reproduced by the simulated evolution of a GA.
In this paper a novel approach for identifying the asymptotic behaviour of non-linear chaotic dynamic systems is proposed. The problem has been faced like an optimization procedure and it has been solved by using the ...
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In this paper a novel approach for identifying the asymptotic behaviour of non-linear chaotic dynamic systems is proposed. The problem has been faced like an optimization procedure and it has been solved by using the genetic algorithm approach. Given the asymptotic time evolution of the state variables of the non-linear system that has to be identified they are used to synchronize another system with the same mathematical model. The difference between the given time evolution and the derived trajectories is used in order to define the functional to be minimized.
This paper presents two intelligent approaches to a production scheduling problem in Flexible Manufacturing systems (FMSs). These are hybrid approaches using a simulator and a genetic algorithm. These approaches are i...
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This paper presents two intelligent approaches to a production scheduling problem in Flexible Manufacturing systems (FMSs). These are hybrid approaches using a simulator and a genetic algorithm. These approaches are integrated to seek efficiently the best combination of dispatching rules in order to obtain an appropriate production schedule under specific performance measures.
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