• 한국국방경영분석학회지
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• 제23권2호
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• pp.103-119
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• 1997

This paper considers the shortest path problem combined with Min-Min-Sum objective for solving the problem of the military logistics. This paper develops a polynomial-time algorithm for the optimal solution. To analyze the real combat situation, the ability time and distance time of communication line are considered. The complexities of algorithm between previous study and the algorithm developed in this paper is presented. Finally we provide a simple example of application with randomly generated problem.

• 산업경영시스템학회지
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• 제42권3호
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• pp.1-7
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• 2019

It is one of the known methods to obtain the optimal solution using the Ant Colony Optimization Algorithm for the Traveling Salesman Problem (TSP), which is a combination optimization problem. In this paper, we solve the TSP problem by proposing an improved new ant colony optimization algorithm that combines genetic algorithm mutations in existing ant colony optimization algorithms to solve TSP problems in many cities. The new ant colony optimization algorithm provides the opportunity to move easily fall on the issue of developing local optimum values of the existing ant colony optimization algorithm to global optimum value through a new path through mutation. The new path will update the pheromone through an ant colony optimization algorithm. The renewed new pheromone serves to derive the global optimal value from what could have fallen to the local optimal value. Experimental results show that the existing algorithms and the new algorithms are superior to those of existing algorithms in the search for optimum values of newly improved algorithms.

• 로봇학회논문지
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• 제16권2호
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• pp.122-129
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• 2021

For the Simultaneous Localization and Mapping (SLAM) problem, a different path results in different SLAM results. Usually, SLAM follows a trail of input data. Active SLAM, which determines where to sense for the next step, can suggest a better path for a better SLAM result during the data acquisition step. In this paper, we will use reinforcement learning to find where to perceive. By assigning entire target area coverage to a goal and uncertainty as a negative reward, the reinforcement learning network finds an optimal path to minimize trajectory uncertainty and maximize map coverage. However, most active SLAM researches are performed in indoor or aerial environments where robots can move in every direction. In the urban environment, vehicles only can move following road structure and traffic rules. Graph structure can efficiently express road environment, considering crossroads and streets as nodes and edges, respectively. In this paper, we propose a novel method to find optimal SLAM path using graph structure and reinforcement learning technique.

• 한국경영과학회지
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• 제27권2호
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• pp.33-49
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• 2002

CBM (Condition-Based Maintenance) has increasingly drawn attention in industry because of its many benefits. CBM Problem Is characterized as a state-dependent scheduling model that demands simultaneous maintenance actions, each for an attribute that influences on machine condition. This problem is very hard to solve within conventional Markov decision process framework. In this paper, we present an intelligent machine maintenance scheduler, for which a new incremental decision tree learning method as evolutionary system identification model and shortest path problem as schedule generation model are developed. Although our approach does not guarantee an optimal scheduling policy in mathematical viewpoint, we verified through simulation based experiment that the intelligent scheduler is capable of providing good scheduling policy that can be used in practice.

• 대한기계학회논문집
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• 제17권5호
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• pp.1183-1192
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• 1993

본 연구에서는 다음과 같은 두가지 관점에서 공구경로 최적화를 위한 기존 방 법의 문제점을 검토하고 이의 개선 방안을 제시하였다. 첫째, 기존의 공구경로 산출 방법에서는 고려되지 않는 공구대의 공구 장착 현황(turret configuration)이 최적화 과정에서 고려되어야 한다. 둘째로, 제작과 관련한 구속조건(manufacturing con- straints)이 최적화 과정에 직접 반영되어야 한다.

• 한국정보과학회논문지:시스템및이론
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• 제34권5_6호
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• pp.195-201
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• 2007

트리의 최소단말경로분할이란 트리를 에지가 서로 소인 단말 노드 간 경로들로 분할하되, 가장 긴 경로의 길이를 최소화하는 문제이다. 본 논문에서는 트리의 최소단말경로분할을 $O({\mid}V{\mid}^2$시간에 구하는 알고리즘을 제시한다. 이 알고리즘은 주어진 최적화 문제를 이에 대응하는 결정 문제, 즉 최소단말경로 분할의 비용이 l 이하인지를 결정하는 문제를 이용한 이진 탐색으로 환원한다. 결정 문제는 트리를 한 차례 순회하는 동안 동적 계획법에 의해 해결된다

• 한국융합학회논문지
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• 제11권2호
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• pp.1-8
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• 2020

본 논문에서는 시간 가중치를 적용하여 각 노드들 간의 중간지점까지의 최적 경로 탐색 기법을 제안한다. 중간지점을 이용하는 서비스들은 주로 사용자들의 위치를 기반으로 하여 제공한다. 위치 기반 탐색 방법은 단순히 위치에 대해서만 고려하기 때문에 시간의 측면에서 효율적이지 못하다는 문제점이 있다. 제안된 방법은 기존의 위치 기반 탐색 방법의 문제점을 해결하기 위해 사용자들의 위치와 중간지점까지의 소요시간을 반영함으로써 각 노드와 중간지점까지의 가중치를 설정하고, 이를 활용하여 최적의 경로를 탐색할 수 있다. 또한, 탐색의 효율성을 증대하기 위해 주어지는 정보들에 적응적으로 가중치를 설정함으로써 높은 정확성을 갖도록 한다. 실험 결과, 제안된 방법은 기존 방법에 비해 중간지점까지의 최적 경로를 효과적으로 찾을 수 있음을 확인하였다.

• 산업경영시스템학회지
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• 제23권59호
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• pp.1-10
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• 2000

The traveling salesman problem is a representative NP-Complete problem. It needs lots of time to get a solution as the number of city increase. So, we need an efficient heuristic algorithm that gets good solution in a short time. Almost edges that participate in optimal path have somewhat low value cost. This paper discusses the property of nearest neighbor and 3-opt. This paper uses nearest neighbor's property to select candidate edge. Candidate edge is a set of edge that has high probability to improve cycle path. We insert edge that is one of candidate edge into intial cycle path. As two cities are connected. It does not satisfy hamiltonian cycle's rule that every city must be visited and departed only one time. This paper uses 3-opt's method to sustain hamiltonian cycle while inserting edge into cycle path. This paper presents a highly efficient heuristic algorithm verified by numerous experiments.

• 한국컴퓨터정보학회논문지
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• 제21권1호
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• pp.131-138
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• 2016

In this paper, we propose a simple linear bottleneck assignment problems (LBAP) algorithm to find the optimal solution. Generally, the LBAP has been solved by threshold or augmenting path algorithm. The primary characteristic of proposed algorithm is derived the optimal solution of LBAP from linear sum assignment problem (LSAP). Firstly, we obtains the solution for LSAP from the selected minimum cost of rows and moves the duplicated costs in row to unselected row with minimum increasing cost in direct and indirect paths. Then, we obtain the optimal solution of LBAP according to the maximum cost of LSAP can be move to less cost. For the 29 balanced and 7 unbalanced problem, this algorithm finds optimal solution as simple.

• 한국정밀공학회지
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• 제13권6호
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• pp.122-127
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• 1996

The achievement of the optimal condition for the task of an industrial articulated robot used in many fields is an important problem to improve productivity. In this paper, a minimum-time trajectory for an articulated robot along the specified path is studied and simulated with a proper example. A general dynamic model of manipulator is represented as a function of path distance. Using this model, the velocity is produced as fast as possible at each point along the path. This minimum-time trajectory planning module together with the existing collision-free path planning modules is utilized to design the optimal path planning of robot in cases where obstacles present.