• Journal of the Korea Society of Computer and Information
• /
• v.15 no.9
• /
• pp.47-55
• /
• 2010

Linear constraint satisfaction optimization problem is a kind of combinatorial optimization problem involving linearly expressed objective function and complex constraints. Integer programming is known as a very effective technique for such problem but require very much time and memory until finding a suboptimal solution. In this paper, we propose a method to improve the search performance by integrating local search and integer programming. Basically, simple hill-climbing search, which is the simplest form of local search, is used to solve the given problem and integer programming is applied to generate a neighbor solution. In addition, constraint programming is used to generate an initial solution. Through the experimental results using N-Queens maximization problems, we confirmed that the proposed method can produce far better solutions than any other search methods.

• Information Systems Review
• /
• v.5 no.2
• /
• pp.203-217
• /
• 2003

Constraint Programming and Optimization have developed in different fields to solve common problems in real world. In particular, constraint propagation and linear Programming are their own fundamental and complementary techniques with the potential for integration to benefit each other. This intersection has evoked the efforts to combine both for a solution method to combinatorial optimization problems. Attempts to combine them have mainly focused on incorporating either technique into the framework of the other with traditional models left intact. This paper argues that integrating both techniques into an old modeling fame loses advantages from another and the integration should be molded in a new framework to be able to exploit advantages from both. The paper propose a declarative modeling framework in which the structure of the constraints indicates how constraint programming and optimization solvers can interact to solve problems.

• Journal of Intelligence and Information Systems
• /
• v.10 no.2
• /
• pp.165-187
• /
• 2004

Constraint Programming in AS and Optimization in OR started and have grown in different backgrounds to solve common decision-making problems in real world. This paper tries to integrate results from those different fields by suggesting a hybrid solver as an integration framework. Starting with an integrating modeling language, a way to implement a hybrid solver will be discussed using Warren's abstract machine and an finite domain constraint programming solver structures. This paper will also propose some issues rising when implementing the hybrid solver and provide their solutions.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.12 no.3
• /
• pp.1-15
• /
• 1992

A Practical and easily applicable methods for the numerical analysis and the optimum design of continuous and horizontally curved two-way slab systems with twelve possible edge conditions are presented. The proposed method for the numerical structural analysis is based on the use of design moment coefficients which are derived from the elastic theory of thin curved plates. The optimum values are selected from within the feasible region in the design space defined by the limit state requirements. The sequential linear programming is introduced as an analytical method of nonlinear optimization. The optimum design variables, including a effective depth and transformed steel ratios per unit width of middle and column strips of slabs, are then determined.

• Proceedings of the Safety Management and Science Conference
• /
• 2000.11a
• /
• pp.91-94
• /
• 2000

본 연구에서는 차량용량이 같지 않은 복수의 다른 종류의 차량을 고려하여, 차량이 이동하면서 배달과 수거를 동시에 수행하고 수거지점으로부터 화물을 수거하여 차고지로 운송하는 귀로 화물(Backhauls)을 갖는 PDP(Pickup and Delivery Problem)문제를 그 연구 대상으로 한다. 동시에 차량을 통해 이동되는 품목이 단일 품목이 아니고, 배달 및 수거시간제약조건을 갖는 다품목 시간제약 수송차량 배차문제를 Time-space network를 이용하여 정수선형계획문제로 정식화한다. 이를 최적화 S/W LINGO를 이용하여 위의 모든 제약조건을 만족하면서 운용되는 차량수와 차량의 이동경로를 최소화하는 해를 구하고, 분석한 내용을 보여주고자 한다. 덧붙여 위 문제의 입·출력자료를 데이터베이스화하여 지리정보시스템(Geographic Information System : GIS)과 통합한 차량운행경로결정 지원시스템을 구축하기 위한 방법을 제시하고자 한다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2011.06a
• /
• pp.286-289
• /
• 2011

제약을 갖는 부분 관찰 의사결정 과정(Constrained Partially Observable Markov Decision Process; CPOMDP)는 정책이 제약(constraint)를 만족하면서 가치 함수를 최적화하도록 일반적인 부분 관찰 의사결정과정(POMDP)을 확장한 모델이다. CPOMDP는 제한된 자원을 가지거나 여러 개의 목적 함수를 가지는 문제를 자연스럽게 모델링할 수 있기 때문에 일반적인 POMDP에 비해 더 실용적인 장점을 가진다. 본 논문에서는 CPOMDP의 확률적 최적 정책 및 근사 최적 정책을 계산할 수 있는 최적 및 근사 동적 프로그래밍 알고리즘을 제안한다. 최적 알고리즘은 동적 프로그래밍의 각 단계마다 미니맥스 이차 제약 계획 문제를 계산해야 하는 반면에 근사 알고리즘은 선형 계획 문제만을 필요로 하는 점-기반(point-based) 가치 업데이트를 이용한다. 실험 결과, 확률적 정책이 결정적(deterministic) 정책보다 더 나은 성능을 보이며, 근사 알고리즘을 통해 계산 시간을 줄일 수 있음을 보였다.

• Proceedings of the Korean Information Science Society Conference
• /
• 1999.10c
• /
• pp.179-181
• /
• 1999

본 논문에서는 내장 실시간 시스템(real-time embedded system)에서의 성능 재조정(re-engineering) 문제를 다룬다. 성능 재조정 문제는 하드웨어와 소프트웨어가 이미 구현된 상태에서 새로운 성능조건이 요구될 때 이를 만족시키도록 시스템을 수정하는 문제이다. 본 논문에서의 성능 요구조건은 시간당 처리량(throughput)이나 입출력 지연시간(input-output latency)등이 고려된다. 제안된 방법은 병목점 분석(bottleneck analysis)과 비선형 최적화를 이용한다. 이를 위해 프로세스 네트워크(process network)로 표현된 시스템 디자인과 태스크 그래프, 태스크 할당(allocation)과 스케쥴링, 그리고 새로운 성능조건인 실시간 처리량을 입력으로 사용한다. 제안된 방법은 두 단계로 구성된다. 첫째, 프로세스 네트워크에서 프로세스의 지연시간을 계산하여 병목이 되는 프로세스를 찾아낸다. 둘째, 프로세싱 요소의 성능 개선율(performance scaling factor)을 변수로 하여 주어진 성능을 만족시키기 위한 시스템 제약조건을 유도한다. 이를 사용하여 하드웨어의 업그레이드 비용을 최소화하도록 제약조건을 풀고 각 프로세싱 요소(processing element)에 필요한 성능개선율을 구한다. 제안된 방법은 기존에 구성된 소프트웨어의 구조를 고치기 않기 때문에 재조정의 시간을 줄일 수 있게 한다.

• Computational Structural Engineering
• /
• v.7 no.1
• /
• pp.117-124
• /
• 1994

Multi-level Multi-objective optimization(MLMO) for reinforced concrete framed structure is performed, and compared with the results of single-level single-objective optimization. MLMO method allows flexibility to meet the design needs such as deflection and cost of structures using weighting factors. Using Multi-level formulation, the numbers of constraints and variables are reduced at each levels, and the optimization formulation becomes simplified. The force approximation method is used to reflect the variation in design variables between the substructures, and thus coupling is maintained. And the linear approximated constraints and objective function are used to reduce the number of structural analysis in optimization process. It is shown that the developed algorithm with move limit can converge effectively to optimal solution.

• ETRI Journal
• /
• v.5 no.3
• /
• pp.3-8
• /
• 1983

In the area of computer network planning, a location-allocation-size problem is involved. Since multi-facility location-allocation-size problems are very complex in formulating a mathematical model, it is a usual practise to adopt alternative approaches, which give no optimal results, instead of the optimal solution by mathematical approach. In this article, however, an attempt is made to formulate a mathematical model for the decision making problem of computer network design.

• Computational Structural Engineering
• /
• v.1 no.1
• /
• pp.87-94
• /
• 1988

The linerization method as one of the recursive quadratic programming method is applied for the optimal design of a large-scale structure supported by Pshenichny's proof of global convergence of the algorithm and convergence rate estimates. The linearization method transforms all constants of the design problem into an equivalent linearized constraint and employs the active-set strategy. This results in substantial computational savings by reducing the number of sate and adjoint to be solved at every design iteration. The illustrative example of plates with beams supported by columns is the typical one of a large-scale structure to give successful optimum solutions with satisfactory convergence criteria. Hopefully, the method may be applicable to all classes of optimization problems.