• 경영과학
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• 제14권1호
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• pp.77-85
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• 1997

This paper proposes an approach for individual selection in genetic algorithms to improve problem solving efficiency and effectiveness. To investigate the utility of combining simulated annealing with genetic algorithm, two experiment are conducted that compare both the conventional genetic algorithm and suggested approach. Result indicated that suggested approach significantly reduced the required time to find optimal solution in moderate-sized problems under the conditions studied. It is also found that quality of the solutions generated by suggested approach in large- sized problems is greatly improved.

• Computers and Concrete
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• 제12권2호
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• pp.109-129
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• 2013

This work presents an approach to model concrete shrinkage. The goal is to permit the concrete industry's experts to develop independent prediction models based on a reduced number of experimental data. The proposed approach combines fuzzy logic and genetic algorithm to optimize the fuzzy decision-making, thereby reducing data collection time. Such an approach was implemented for an experimental data set related to self-compacting concrete. The obtained prediction model was compared against published experimental data (not used in model development) and well-known shrinkage prediction models. The predicted results were verified by statistical analysis, which confirmed the reliability of the developed model. Although the range of application of the developed model is limited, the genetic-fuzzy approach introduced in this work proved suitable for adjusting the prediction model once additional training data are provided. This can be highly inviting for the concrete industry's experts, since they would be able to fine-tune their models depending on the boundary conditions of their production processes.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 D
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• pp.1106-1108
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• 1997

This paper presents a new approach on genetic algorithms to economic dispatch problem for valve point discontinuities. Proposed approach in this paper on genetic algorithms improves the performance to solve economic dispatch problem for valve point discontinuities through combination in penalty function with death penalty, generation-apart elitism, atavism and heuristic crossover. Numerical results on an actual utility system consisted of 13 thermal units show that the proposed approach is faster and robuster than classical genetic algorithm.

• Journal of Advanced Marine Engineering and Technology
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• 제22권5호
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• pp.687-692
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• 1998

Test pattern generation is one of most difficult problems encountered in automating the design of logic circuits. The goal is to obtain the highest fault coverage with the minimum number of test patterns for a given circuit and fault set. although there have been many deterministic algorithms and heuristics the problem is still highly complex and time-consuming. Therefore new approach-es are needed to augment the existing techniques. This paper considers the problem of test pattern improvement for combinational circuits as a restricted subproblem of the test pattern generation. The problem is to maximize the fault coverage with a fixed number of test patterns for a given cir-cuit and fault set. We propose a new approach by use of a genetic algorithm. In this approach the genetic algorithm evolves test patterns to improve their fault coverage. A fault simulation is used to compute the fault coverage of the test patterns Experimental results show that the genetic algorithm based approach can achieve higher fault coverages than traditional techniques for most combinational circuits. Another advantage of the approach is that the genetic algorithm needs no detailed knowledge of faulty circuits under test.

• 대한전기학회논문지
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• 제41권9호
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• pp.1095-1103
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• 1992

An approach to fuse the fuzzy inference system which is able to deal with imprecise and uncertain information and genetic algorithms which display the excellent robustness in complex optimization problems is presented in this paper. In order to combine genetic algorithms and fuzzy inference engine effectively the new reasoning method is suggested. The efficient identification method of fuzzy rules is proposed through the adjustment of search areas of genetic algorithms. The feasibilty of the proposed approach is evaluated through simulation.

• Molecules and Cells
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• 제45권2호
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• pp.93-97
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• 2022

Evasion, approach and predation are examples of innate behaviour that are fundamental for the survival of animals. Uniting these behaviours is the assessment of threat, which is required to select between these options. Far from being comprehensive, we give a broad review over recent studies utilising optic techniques that have identified neural circuits and genetic identities underlying these behaviours.

• 경영과학
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• 제14권2호
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• pp.47-61
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• 1997

This paper considers the parallel machines scheduling problem characterized as a multi-objective combinatorial problem. As this problem belongs to the NP-complete problem, genetic algorithms are applied instead of the traditional analytical approach. The purpose of this study is to show how the problem can be effectively solved by using genetic algorithms with a permutation approach. First, a permutation representation which can effectively represent the chromosome is introduced for this problem . Next, a schedule builder which employs the combination of scheduling theories and a simple heuristic approach is suggested. Finally, through the computer experiments of genetic algorithm to test problems, we show that the niche formation method does not contribute to getting better solutions and that the PMX crossover operator is the best among the selected four recombination operators at least for our problem in terms of both the performance of the solution and the operational convenience.

• 산업경영시스템학회지
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• 제35권1호
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• pp.10-15
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• 2012

This paper considers an economic design problem of a tree-based network which is a kind of computer network. This problem can be modeling to be an objective function to minimize installation costs, on the constraints of spanning tree and maximum traffic capacity of sub tree. This problem is known to be NP-hard. To efficiently solve the problem, a tabu list coupled genetic algorithm approach is proposed. Two illustrative examples are used to explain and test the proposed approach. Experimental results show evidence that the proposed approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic algorithm approach.

• 한국경영과학회지
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• 제14권2호
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• pp.47-47
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• 1989

This paper considers the parallel machines scheduling problem characterized as a multi-objective combinatorial problem. As this problem belongs to the NP-complete problem, genetic algorithms are applied instead of the traditional analytical approach. The purpose of this study is to show how the problem can be effectively solved by using genetic algorithms with a permutation approach. First, a permutation representation which can effectively represent the chromosome is introduced for this problem . Next, a schedule builder which employs the combination of scheduling theories and a simple heuristic approach is suggested. Finally, through the computer experiments of genetic algorithm to test problems, we show that the niche formation method does not contribute to getting better solutions and that the PMX crossover operator is the best among the selected four recombination operators at least for our problem in terms of both the performance of the solution and the operational convenience.

• 소성∙가공
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• 제5권4호
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• pp.269-280
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• 1996

A new approach to die shape optimal design in extrusion is presented. The approach consists of a FEM analysis model to predict the value of the objective function a design model to relate the die profile with the design variables and a genetic algorithm based optimaization procedure. The approach was described in detail with emphasis on our modified micro genetic algorithm. Comparison with theoretical solutions was made to examine the validity of the predicted optimal die shapes. The approach was then applied to revealing the optimal die shapes with regard to various objective functions including those for which the design sensitivities can not be deter-mined analytically.