• Industrial Engineering and Management Systems
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• v.14 no.1
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• pp.11-21
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• 2015

The purpose of this research is to develop algorithms using the Differential Evolution Algorithm (DE) to solve a multi-objective, sources and stages location-allocation problem. The development process starts from the design of a standard DE, then modifies the recombination process of the DE in order improve the efficiency of the standard DE. The modified algorithm is called modified DE. The proposed algorithms have been tested with one real case study (large size problem) and 2 randomly selected data sets (small and medium size problems). The computational results show that the modified DE gives better solutions and uses less computational time than the standard DE. The proposed heuristics can find solutions 0 to 3.56% different from the optimal solution in small test instances, while differences are 1.4-3.5% higher than that of the lower bound generated by optimization software in medium and large test instances, while using more than 99% less computational time than the optimization software.

• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.63-65
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• 2006

• The Journal of Korean Association of Computer Education
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• v.19 no.1
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• pp.101-109
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• 2016

Designing algorithms is a very important learning process in computational thinking education because it requires learner's logical and procedural thinking. But the case studies that have topics of algorithms learning and students' types of errors in learning algorithms are not enough. So the purpose of this study is to analyze students' errors that discovered in the process of learning three control structures of programming using flowchart and provide types of errors in designing algorithms. Results about tests of three types of control structures in university student's algorithms learning class showed different cases of types of errors; types of sequential control error are not presented in the class, types of conditional control error are presented in the case of setting the conditions of nested conditional control, and types of iterative control are showed in the many cases of iterative conditions, statements of single and nested iterative control structure. The results of study will be a good case study about teaching designing algorithms of computational thinking education in elementary, secondary school and university.

• Korean Journal of Computational Design and Engineering
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• v.1 no.3
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• pp.234-241
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• 1996

Recently, Genetic Algorithms(GAs), which consist of genetic operators named selection crossover and mutation, are widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GAs are very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GAs. So, they can be easily applicable to wide territory of design optimization problems. Also, virtue to multi-point search procedure, they have higher probability of convergence to global optimum compared with traditional techniques which take one-point search method. The introduction of basic theory on GAs, and the application examples in combination optimization of ten-member truss structure are presented in this paper.

• Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.24-36
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• 2016

During the past decade, solving complex optimization problems with metaheuristic algorithms has received considerable attention among practitioners and researchers. Hence, many metaheuristic algorithms have been developed over the last years. Many of these algorithms are inspired by various phenomena of nature. In this paper, a new population based algorithm, the Lion Optimization Algorithm (LOA), is introduced. Special lifestyle of lions and their cooperation characteristics has been the basic motivation for development of this optimization algorithm. Some benchmark problems are selected from the literature, and the solution of the proposed algorithm has been compared with those of some well-known and newest meta-heuristics for these problems. The obtained results confirm the high performance of the proposed algorithm in comparison to the other algorithms used in this paper.

• Industrial Engineering and Management Systems
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• v.11 no.3
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• pp.215-223
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• 2012

This paper focuses on three very similar evolutionary algorithms: genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE). While GA is more suitable for discrete optimization, PSO and DE are more natural for continuous optimization. The paper first gives a brief introduction to the three EA techniques to highlight the common computational procedures. The general observations on the similarities and differences among the three algorithms based on computational steps are discussed, contrasting the basic performances of algorithms. Summary of relevant literatures is given on job shop, flexible job shop, vehicle routing, location-allocation, and multimode resource constrained project scheduling problems.

• 한국전산유체공학회:학술대회논문집
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• 2006.05a
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• pp.178-181
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• 2006

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.354-366
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• 1993

In this paper, new algorithms for solving the multiple traveling salesman problem with time windows are presented. These algorithms are based on the flow based algorithms for solving the vehicle scheduling problem. Computational results on problems up to 750 customers indicate that these algorithms produce superior results to existing heuristic algorithms for solving the vehicle routing problems when the time windows are 'tight enough' where 'tight enough' is based on a metric proposed by desrosiers et al.(1987).

• The Pure and Applied Mathematics
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• v.15 no.3
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• pp.229-243
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• 2008

This paper is intended to clarify and verify two representation algorithms computing representations of elements of free groups generated by two linear fractional transformations. Moreover in practice some parts of the two algorithms are modified for computational efficiency. In particular the justification of the algorithms has been rigorously done by showing how both algorithms work correctly and efficiently according to inputs with some properties of the two linear fractional transformations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.11
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• pp.2131-2138
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• 2011

GPS is vulnerable to jamming because of extremely low signal power. Many anti-jamming techniques are studied for complement this vulnerability. Anti-jamming techniques using array antenna are most effective technique and these techniques are required the DOA estimates. MUSIC algorithm and Root-MUSIC Algorithm are typical algorithms used in DOA estimation. Two algorithms have different characteristics, so the choice of an algorithm may depends on many factors such as the environment and the system requirements. The analysis and performance comparison of both algorithms is necessary to choose the best method to apply. This paper summarizes the theory of MUSIC and Root-MUSIC algorithms. And this paper extends both algorithm to estimate two-dimensional angles. The software simulator of both algorithms are implemented to evaluate the performance. Root-MUSIC algorithm has the computational advantage on ULA. MUSIC algorithm is applicable to any antenna array. MUSIC shows better estimation performance when number of array element is small while the computational load of MUSIC is much higher than Root-MUSIC.