• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1089-1095
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• 2004

The genetic algorithms have been used to take a near optimal solution because The generation of the optimal Steiner tree from a given network is NP-hard problem,. The chromosomes in genetic algorithm are represented with the floating point representation instead of the existing binary string for solving this problem. A spanning tree was obtained from a given network using Prim's algorithm. Then, the new Steiner point was computed using genetic algorithm with the chromosomes in the floating point representation, and it was added to the tree for approaching the result. After repeating these evolving steps, the near optimal Steiner tree was obtained. Using this method, the tree is quickly and exactly approached to the near optimal Steiner tree compared with the existing genetic algorithms using binary string.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.10
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• pp.562-574
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• 2004

We address the problem of energy-optimal voltage scheduling for fixed-priority hard real-time systems. First, we prove that the problem is NP-hard. Then, we present a fully polynomial time approximation scheme (FPTAS) for the problem. for any $\varepsilon$>0, the proposed approximation scheme computes a voltage schedule whose energy consumption is at most (1+$\varepsilon$) times that of the optimal voltage schedule. Furthermore, the running time of the proposed approximation scheme is bounded by a polynomial function of the number of input jobs and 1/$\varepsilon$. Experimental results show that the approximation scheme finds more efficient voltage schedules faster than the best existing heuristic.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.341-346
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• 2008

Minimum Weight Triangulation (MWT) problem is an optimization problem searching for the triangulation of a given graph with minimum weight. Like many other graph problems this problem is also known to be NP-hard for general graphs. Several heuristic algorithms have been proposed for this problem including simulated annealing and genetic algorithm. In this paper, we propose a new genetic algorithm called GA-FF and show that the performance of the proposed genetic algorithm outperforms the previous one.

• Bulletin of the Korean Chemical Society
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• v.35 no.9
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• pp.2621-2624
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• 2014

The rapid and spontaneous adsorption of proteins on nanoparticle (NP) surfaces in biological fluids such as blood is an important phenomenon as it possibly determines "what the cells see" and, thus, the fates of NPs in living organisms. In order to quantitatively understand protein coronas at the molecular level, we investigated human serum albumin (HSA) coronas that were produced on silica NPs of 20 nm and 50 nm diameters using conventional gel electrophoresis. Analysis of the concentration dependence of protein adsorption showed that HSA coronas preferentially formed a monolayer on silica NPs and revealed the presence of hard protein coronas. HSA adsorption was clearly dependent on NP size, and this might be due to the different surface curvatures of NPs of different sizes.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.109-116
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• 2007

Nowadays, with the proliferation of Web services, developer and user can implement a complex application by composing registered Web services. In this trend, the quality of service of a composite Web service is of crucial importance for today's Service Oriented Computing (SOC) environment. But the global optimization of a composite Web service satisfying given QoS is classified to NP-hard problem. To solve this problem, we propose K-way Super node approach and show the effect of it from experimental results.

• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.73-82
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• 2011

There are a lot of people trying to solve the Traveling Salesman Problem (TSP) by using the Meta Heuristic Algorithms. TSP is an NP-Hard problem, and is used in testing search algorithms and optimization algorithms. Also TSP is one of the models of social problems. Many methods are proposed like Hybrid methods and Custom-built methods in Meta Heuristic. In this paper, we propose the S-MINE Algorithm to use the MINE Algorithm introduced in 2009 on the TSP.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.130-133
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• 2007

본 논문에서는 서로 다른 주문들의 일부를 일괄적으로 처리할 수 있을 때, 최대 개수의 작업 단위로 최대한 많은 수의 주문을 처리하는 문제를 다룬다. 무향그래프와 배치 크기 $\lambda$로 표현되는 이 문제의 일반적인 경우는 NP-hard이며, 나무일 때 다항시간 안에 최적해를 찾을 수 있음이 증명되어 있다. 본 논문에서는 이분 그래프의 경우에도 NP-hard임을 보이고, 이 경우에 절대근사 알고리즘과 상대근사 알고리즘을 제시한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.99-102
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• 2000

전통적인 job shop 일정계획문제는 NP_hard 문제로 조합최적화 문제이다 일반적인 가정은 job이 방문하는 기계들의 경로가 고정되어 있다는 것이다. 경로 유연성을 가지는 job shop 일정계획문제는 job이 방문하는 기계들의 경로가 고정되어져 있지 않다는 것이다. 이러한 경우에 전통적인 job shop 문제를 복잡하게 만든다. 경로 유연성을 가지는 job shop 문제도 NP-hard 문제이다. 그러므로 휴레스틱이나 AI 기법들을 사용하는 하는 것이 불가피하게 되었다. 유전 알고리즘은 매우 복잡한 조합 최적화문제인 job shop 일정계획문제에 적용되어지고 있다. 이 논문은 최대완료시간(makespan)으로 경로 유연성을 가지는 job shop 일정계획문제를 풀기 위한 유전 알고리즘을 제시하고자 한다. 먼저 경로 유연성을 가지는 job shop 일정계획문제에 대한 정의를 내리고 유전 알고리즘을 구축하기 위한 첫 단계로 유전적 표현 즉, 개체 표현방법에 대해 설명하고 유전 연산자의 소개 그리고 알고리즘 재생과정을 제시하고 수치실험을 통해 알고리즘이 양질의 일정계획을 찾을 수 있다는 것을 보이고자 한다.

• Korean Management Science Review
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• v.29 no.2
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• pp.143-155
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• 2012

The purpose of this study is to formulate and solve the scheduling problem to heat-treatment process in forging process and apply it to industries. Heat-treatment is a common process in manufacturing heavy forged products in ship engines and wind power generators. Total complete time of the schedule depends on how to group parts and assign them into heat furnace. Efficient operation of heat-treatment process increases the productivity of whole production system while scheduling the parts into heat-treatment furnace is a combinatorial problem which is known as an NP-hard problem. So the scheduling, on manufacturing site, relies on engineers' experience. To improve heat-treatment process schedule, this study formulated it into an MIP mathematical model which minimizes total complete time. Three methods were applied to example problems and the results were compared to each other. In case of small problems, optimal solutions were easily found. In case of big problems, feasible solutions were found and that feasible solutions were very close to lower bound of the solutions. ILOG OPL Studio 5.5 was used in this study.

• Management & Information Systems Review
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• v.34 no.2
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• pp.67-78
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• 2015

In this paper, we consider a scheduling problem of printed circuit board production process with setup cost depending job sequence. Given a set of PCBs, these are produced in single surface mounting device. The problem is to define job sequence with the objective of minimizing the total seutp cost. We propose a mathematical formulation and the problem is proven to be NP-hard. So, a meta heuristic based on genetic algorithm is developed.