• Title/Summary/Keyword: NP-Complete

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A Modified Hopfield Network and It's application to the Layer Assignment (Hopfield 신경 회로망의 개선과 Layer Assignment 문제에의 응용)

  • 김규현;황희영;이종호
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.40 no.2
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    • pp.234-237
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    • 1991
  • A new neural network model, based on the Hopfield crossbar associative network, is presented and shown to be an effective tool for the NP-Complete problems. This model is applied to a class of layer assignment problems for VLSI routing. The results indicate that this modified Hopfield model, improves stability and accuracy.

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Efficient Application to SAT Using DNF (DNF를 이용한 SAT의 효율적 적용)

  • 남명진;최진영
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.04a
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    • pp.881-883
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    • 2003
  • 하드웨어 검증과 모델 체킹 등의 분야에서, SAT(satisfiability problem)나 항진 명제 검사(tautology checking)는 매우 중요한 문제이다. 그러나 이들은 모두 NP-complete 문제이므로 그 복잡도가 매우 크다. 이를 해결하기 위해 여러 가지 연구가 이루어져 왔으며, 여러 효율적인 알고리즘이 존재한다. 이러한 알고리즘은 대부분 일반 표현식을 CNF(conjunctive normal form)로 바꾸어 입력 형식으로 사용한다. 이 논문에서는 일반 표현식을 입력으로 받아 DNF로 변환한 뒤 DNF의 특성을 이용하여 SAT를 검사하는 효율적인 방법을 제시한다.

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Smoothing Algorithm for DNA Code Optimization (Smoothing Algorithm을 이용한 DNA 코드 최적화)

  • 윤문식;한치근
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10a
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    • pp.64-66
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    • 2003
  • DNA(Deoxyribo Nucleic Acid)컴퓨팅은 생체분자를 계산의 도구로 이용하는 새로운 계산 방법으로 DNA 정보 저장능력과 DNA의 상보적인 관계를 이용하여 연산을 수행하는 방법이다. 최근에는 DNA 분자들이 갖는 강력한 병렬성을 이용하여 NP-Complete 문제에 적용하는 연구가 많이 시도되고 있다. Adleman이 DNA 컴퓨팅을 이용해 해결한 HPP(Hamilton Path Problem)와는 달리 TSP(Traveling Salesman Problem)는 간선에 가중치가 추가되었기 때문에 DNA 염기배열로 표현하기가 어렵고 또한 염기배열의 길이를 줄이기 위해 고정길이 염기배열을 사용할 경우 가중치가 커지면 효율적이지 못하다. 본 논문에서는 스무딩 알고리즘(smoothing algorithm)을 사용하여 간선의 가중치를 일정한 비율로 줄인 다음 유전자 알고리즘을 사용하여 최적의 염기배열을 찾는 방법을 제안하였다.

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Implementation and Experiments of SAT preprocessor (SAT Preprocessor의 구현 및 실험)

  • 남명진;최진영;곽희환
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10a
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    • pp.517-519
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    • 2003
  • 하드웨어 검증과 모델 체킹 등의 분야에서, SAT(satisfiability problem)나 항진 명제 검사(tautology checking)는 매우 중요한 문제이다. 그러나 이들은 모두 NP-complete 문제이므로 그 복잡도가 매우 크다. 이를 해결하기 위한 여러 연구가 진행되고 있고, 그 결과 성능이 좋은 solver들이 개발되었다. 하지만 문제가 커질수록 solver의 처리 시간이 급격하게 증가한다. 이 논문에서는 solver가 복잡한 문제를 더 효율적으로 풀기 위해 논문“Local search for Boolean relations on the basis of unit propagation”[5]에서 제안된 preprocessor(전처리기), P_EQ의 개념을 설명하고, 실험을 통한 결과를 제시한다.

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A Tabu Search Methods for Minimizing Mean Tardiness In Parallel Machines Scheduling

  • Chun Tai-Woong;Park Hai-Chun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.23 no.60
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    • pp.67-72
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    • 2000
  • In this paper we consider to parallel machines scheduling problems for minimizing mean tardiness that is known NP-complete. This problems is classified into two cases, one of which is the case which processing time are identical and the other, nonidentical. A Tabu Search method is applied to the problems considered in this paper to get an improved solution. To this end, we design move attribute, Tabu attribute and Tabu tenure, and thereafter perform the experiments to the problems.

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A Heuristic Algorithm for Asymmetric Traveling Salesman Problem using Hybrid Genetic Algorithm (혼합형 유전해법을 이용한 비대칭 외판원문제의 발견적해법)

  • 김진규;윤덕균
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.18 no.33
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    • pp.111-118
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    • 1995
  • This paper suggests a hybrid genetic algorithm for asymmetric traveling salesman problem(TSP). The TSP was proved to be NP-complete, so it is difficult to find optimal solution in reasonable time. Therefore it is important to develope an algorithm satisfying robustness. The algorithm applies dynamic programming to find initial solution. The genetic operator is uniform order crossover and scramble sublist mutation. And experiment of parameterization has been performed.

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An Expert System for Job Shop Scheduling (전문가 시스템을 이용한 Job Shop 일정계획)

  • Oh, Seung-Joon
    • Journal of Industrial Convergence
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    • v.1 no.2
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    • pp.69-79
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    • 2003
  • In order to solve scheduling, many techniques including optimization and heuristics methods have been proposed. However, these conventional approaches are usually inadequate to obtain a satisfactory solution because of a NP-Complete which requires extensive computation effort. The aim of this paper is to develop an expert system for job shop scheduling using an AI technique. Through this system, the user can choose one of several performances. If one performance is chosen, then the system solves a scheduling in order to satisfy that performance. Then, this system decides urgent job. This system can utilize production resources efficiently and minimize work-in-process inventories and tardy jobs.

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PACKING LATIN SQUARES BY BCL ALGEBRAS

  • LIU, YONGHONG
    • Journal of applied mathematics & informatics
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    • v.40 no.1_2
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    • pp.133-139
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    • 2022
  • We offered a new method for constructing Latin squares. We introduce the concept of a standard form via example for Latin squares of order n and we also call it symmetric BCL algebras matrix, and thereby become BCL algebra representations of the picture of Latin squares. Our research shows that some new properties of the Latin squares with BCL algebras are in ℤn.

Location Area Planning Using Ant Colony Optimization (개미군 최적화 방법을 이용한 Location Area Planning)

  • Kim, Sung-Soo;Kim, Hyung-Jun;Kim, Ki-Dong
    • Korean Management Science Review
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    • v.25 no.2
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    • pp.73-80
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    • 2008
  • The location area planning is to assign cells to the location areas of a wireless communication network in an optimum manner. The two important cost components are cost of location update and cost of paging that are of conflicting in nature; i.e., minimizing the registration cost might increase the search cost. Hence, it is important to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking cost is a minimum. The complete mobile network is divided into location areas. Each location area consists of a group of cells. In fact this is shown to be an NP-complete problem in an earlier study. In this paper, we use an ant colony optimization method to obtain the best/optimal group of cells for a given a network.

A Study on Optimal Layout of Two-Dimensional Rectangular Shapes Using Neural Network (신경회로망을 이용한 직사각형의 최적배치에 관한 연구)

  • 한국찬;나석주
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.17 no.12
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    • pp.3063-3072
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    • 1993
  • The layout is an important and difficult problem in industrial applications like sheet metal manufacturing, garment making, circuit layout, plant layout, and land development. The module layout problem is known to be non-deterministic polynomial time complete(NP-complete). To efficiently find an optimal layout from a large number of candidate layout configuration a heuristic algorithm could be used. In recent years, a number of researchers have investigated the combinatorial optimization problems by using neural network principles such as traveling salesman problem, placement and routing in circuit design. This paper describes the application of Self-organizing Feature Maps(SOM) of the Kohonen network and Simulated Annealing Algorithm(SAA) to the layout problem of the two-dimensional rectangular shapes.