• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.172-174
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• 1996

This paper presents a new approach on genetic algorithms to economic dispatch problem for valve point discontinuities. Although it has been already shown that genetic algorithm was more powerful to economic dispatch problem for valve point discontinuities than other optimization algorithms, 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 and heuristic crossover. Numerical results on an actural utility system consisted of 13 thermal units show that the proposed approach is faster and robuster than the classical genetic algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.3
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• pp.329-338
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• 2007

This paper presents a dispatching algorithm for nonidentical parallel machines problem considering rework, sequence dependent setup times and release times. For each pair of a machine and a job type, rework probability of each job on a machine can be known through historical data acquisition. The heuristic scheduling scheme named by EDDR (Earliest Due Date with Rework probability) algorithm is proposed in this paper making use of the rework probability. The proposed dispatching algorithm is measured by two objective function value: 1) total tardiness and 2) the number of reworked jobs, respectively. The extensive computational results show that the proposed algorithm gives very efficient schedules superior to the existing dispatching algorithms.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.460-470
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• 1996

In this paper, we describe the programming methodology which can produce computer Go.After computer Go program with the rules of Go determines a territory for itself, it must evaluate the exact next move. The common design principle of computer Go is to combine such heuristic elements as pattern match, alpha-beta pruning and influence function. In this study, we introduce many other approaches and their results on computer Go, and then show data structures and algorithms to implement computer Go project.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.326-328
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• 1998

This paper presents an optimal fuzzy power system stabilizer to damp out low frequency oscillation. The fuzzy logic controllers has been applied to a power system stabilizing controllers. But the design of a fuzzy logic power system stabilizer relies on empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This paper presents the optimal design method of the fuzzy logic stabilizer using the genetic algorithm, which is the optimization method based on the mechanics of natural selection and natural genetics. The proposed method tunes the parameters of the fuzzy logic stabilizer in order to minimize the consuming time during the design process. In this paper, the proposed method tunes the shape of membership function of the fuzzy variables. The proposed system is applied to the one-machine infinite-bus model of a power system. Through the case study, the efficiency of the fuzzy stabilizing controller tuned by genetic algorithm is verified.

• Journal of the military operations research society of Korea
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• v.28 no.2
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• pp.116-124
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• 2002

In just-in-time production systems, U-shaped production lines rather than traditional straight lines are often adopted since they have some advantages. The advantages of U-lines over straight lines are that the workstations required can be reduced and the necessary number of workers can be easily adjusted when the demand rates are changed. In this paper, we present a new genetic algorithm(GA) to minimize the number of workstations primarily and improve the work relatedness secondarily in the U-line production systems. Also, a new heuristic method is presented according to the work related factors and characteristics of U-line balancing. Some major aspects of the proposed GA are discussed, with emphasis on representation, decoding and evaluation function. Extensive experiments are carried out on well-known test-bed problems in the literature to verify the performance of our algorithm . The computational results show that our algorithm is a promising alternative to existing heuristics.

• Asia pacific journal of information systems
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• v.1 no.1
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• pp.117-145
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• 1991

IS changeback is regarded as an offective way to control the usage of computers and communication systems which are very much limited resources and whose costs are very high, In this paper, the problem of combining the optimal chargeback system which guarantees the efficiency with the Rawls'(1971) concept of fairness. Primary conclusion of this paper is that if the value function which represents the contributions of IS user to the firm's profit is evidit and there is no uncertainty about this contribution information, optimality can be achived without any loss of fairness using full cost allocation pricing. But if there is no significant differences among contribution of each user and there is no significant differences among users because of the managerial arbitrariness, From this point of view contingent chargeback system with which manager can find the golden middle between optimality and fairness by adjusting the 'efficiency coefficient' according to his/her organizational characterisics and environments is proposed. A heuristic of finding the appropriate efficiency coefficient is also suggested.

• Structural Engineering and Mechanics
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• v.55 no.6
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• pp.1223-1239
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• 2015

A method for structural damage identification based on Chaotic Artificial Bee Colony (CABC) algorithm is presented. ABC is a heuristic algorithm with simple structure, ease of implementation, good robustness but with slow convergence rate. To overcome the shortcoming, the tournament selection mechanism is chosen instead of the roulette mechanism and chaotic search mechanism is also introduced. Residuals of natural frequencies and modal assurance criteria (MAC) are used to establish the objective function, ABC and CABC are utilized to solve the optimization problem. Two numerical examples are studied to investigate the efficiency and correctness of the proposed method. The simulation results show that the CABC algorithm can identify the local damage better compared with ABC and other evolutionary algorithms, even with noise corruption.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.35
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• pp.47-52
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• 1995

The aim of this paper is to suggest the cutting stock problems which are two-dimensional in form, but can be treated as the optimization methods for one-dimensional cutting stock problem by exploiting the length requirement of the products. The solution method consists of two stages. The first calculates the number of roll pieces of each size. Next, 1-dimensional cutting stock model is set up. One heuristic method to calculate the number of each roll is suggested. The trim loss minization criteria are used to design the objective function. This model can be solved by the conventional cutting stock procedures based on enumerating the possible cutting patterns.

• Journal of Industrial Convergence
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• v.3 no.1
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• pp.19-31
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• 2005

This paper deals with the sequencing problem in the operation of the manufacturing systems with the constraint of buffer capacity. Some of studies for this theme have been progressed for several years. And then most of them considered only one objective, such as maximum lateness, machine utilization, makespan, mean flowtime and so on. This study deal with two objectives of the delivery for customers and the idle time of machines for producers. For the decision of sequence, the utility function is used. The developed heuristic algorithm presents a good solution. Through a numerical example, the procedures of the job sequencing is explained.

• Advances in robotics research
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• v.2 no.3
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• pp.247-257
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• 2018

Various studies have been performed to coordinate robots in transporting objects and different artificial intelligence algorithms have been considered in this field. In this paper, we investigate and solve Multi-Robot Transportation problem by using a combined auction algorithm. In this algorithm each robot, as an agent, can perform the auction and allocate tasks. This agent tries to clear the auction by studying different states to increase payoff function. The algorithm presented in this paper has been applied to a multi-robot system where robots are responsible for transporting objects. Using this algorithm, robots are able to improve their actions and decisions. To show the excellence of the proposed algorithm, its performance is compared with three heuristic algorithms by statistical simulation approach.