• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.127-135
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• 2008

Generally, optimum shortest path algorithms adopt single attribute objective among several attributes such as travel time, travel cost, travel fare and travel distance. On the other hand, multi-objective shortest path algorithms find the shortest paths in consideration with multi-objectives. Up to recently, the most of all researches about multi-objective shortest paths are proceeded only in single transportation mode networks. Although, there are some papers about multi-objective shortest paths with multi-modal transportation networks, they did not consider transfer problems in the optimal solution level. In particular, dynamic programming method was not dealt in multi-objective shortest path problems in multi-modal transportation networks. In this study, we propose a multi-objective shortest path algorithm including dynamic programming in order to find optimal solution in multi-modal transportation networks. That algorithm is based on two-objective node-based label correcting algorithm proposed by Skriver and Andersen in 2000 and transfer can be reflected without network expansion in this paper. In addition, we use non-dominated paths and tree sets as labels in order to improve effectiveness of searching non-dominated paths. We also classifies path finding attributes into transfer and link travel attribute in limited transit networks. Lastly, the calculation process of proposed algorithm is checked by computer programming in a small-scaled multi-modal transportation network.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.55-61
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• 2021

As the demand for distance education increases, it is necessary to present a problem solving path through a learning tracking algorithm in order to support the efficient learning of learners. In this paper, we proposed a problem solving path of various difficulty levels in various subjects by supplementing the existing learning tracking algorithm. Through the data set obtained through the path for solving the learner's problem, the path through the prim's minimum Spanning tree was secured, and the optimal problem solving path through the recursive neural network was suggested through the path data set. As a result of the performance evaluation of the contents proposed in this paper, it was confirmed that more than 52% of the test subjects included the problem solving path suggested in the problem solving process, and the problem solving time was also improved by more than 45%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.71-73
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• 2017

논문에서는 최적화 문제를 해결하는 기법의 하나인 $A^*$와 유전자 알고리즘을 이용하여 모든 노드를 탐색하여 최적의 경로를 도출하는 최적화 경로 탐색 방법을 제안한다. 경로를 도출하기 위해 $A^*$ 알고리즘을 적용하여 출발지 노드로부터 중간 경로 노드까지의 거리를 측정하여 개체를 생성한다. 출력 노드들을 도출하기 위해 생성된 개체를 적합도 함수에 적용하여 적합도를 계산한다. 계산된 적합도 값에 따라 교배를 할 노드 및 교배 지점을 선택한다. 선택된 노드와 교배 지점을 이용하여 개체들을 교배한다. 교배를 통해 새로운 개체를 생성한다. 새로운 개체가 적합도 조건에 만족하면 출력 노드로 도출하고, 다음 출력 노드를 도출하기 위한 출발지 노드로 선택한다. 이러한 과정을 반복하여 모든 출력 노드를 도출한다. 제안된 방법을 경로 탐색 문제를 대상으로 실험한 결과, $A^*$ 알고리즘만을 이용한 경우보다 제안된 방법이 경로 탐색 문제에 있어서 최적화된 거리를 기반으로 경로를 탐색하는 것을 확인하였다.

• Annual Conference of KIPS
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• 2019.05a
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• pp.371-374
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• 2019

PDA나 휴대폰 단말로 여러 속성의 데이터를 이용하여 사용자에게 필요한 정보를 제공하는 위치기반 서비스는 물류/운송 정보 서비스, 버스/지하철 노선 안내 서비스 등에 사용된다. 여기에서 제공하는 데이터들을 최적 경로를 구하는 외판원 순회문제 (Traveling Salesman Problem)에 사용한다면 더 정확한 경로 서비스 제공이 가능하다. 하지만 데이터의 수가 많아질수록 비교 횟수가 기하급수적으로 늘어나는 외판원 순회 알고리즘의 특성상 일반 단말기에서 활용하기에는 배터리의 제약이 따른다. 본 논문에서는 이와 같은 단점을 해결하기 위해서 최적 경로의 후보군을 줄일 수 있는 스카이라인 질의를 이용하여 n차원 속성에 대한 최적 경로 알고리즘을 제안한다. 실험에서 정확도와 오차율을 통해 제안한 방식의 유용성을 보였으며 기존방식과 연산시간 차이를 비교하여 다차원방식의 효율성을 나타내었다.

• Journal of the military operations research society of Korea
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• v.33 no.2
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• pp.31-47
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• 2007

The main purpose of this study is to find out the best solution of the vehicle routing problem with hard time window by using both genetic algorithm and heuristic. A mathematical programming model was also suggested in the study. The suggested mathematical programming model gives an optimal solution by using ILOG-CPLEX. This study also suggests a hybrid genetic algorithm which considers the improvement of generation for an initial solution by savings heuristic and two heuristic processes. Two heuristic processes consists of 2-opt and Or-opt. Hybrid genetic algorithm is also compared with existing problems suggested by Solomon. We found better solutions rather than the existing genetic algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.17-24
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• 2020

The traveling salesman problem is an algorithmic problem tasked with finding the shortest route that a salesman visits, visiting each city and returning to the started city. Due to the exponential time complexity of TSP, it's hard to implement on cases like amusement park or delivery. Also, TSP is hard to meet user's demand that is associated with multi-dimensional attributes like travel time, interests, waiting time because it uses only one attribute - distance between nodes. This paper proposed Top-n Skyline-Multi Dimension TSP to resolve formerly adverted problems. The proposed algorithm finds the shortest route faster than the existing method by decreasing the number of operations, selecting multi-dimensional nodes according to the dominance of skyline. In the simulation, we compared computation time of dynamic programming algorithm to the proposed a TS-MDT algorithm, and it showed that TS-MDT was faster than dynamic programming algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.734-740
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• 2003

링 루팅 및 파장할당 문제는 최근 활발하게 구축되는 있는 WDM 링의 설계 및 운용에 있어서 매우 중요한 문제이다. 이 문제는 링 상의 노드 쌍간에 단위수요가 주어졌을 때, 각 수요들을 링 상의 두 가지 가능한 경로 중 하나로 보내기 위한 광경로의 설정과 설정된 광경로에 파장을 할당하는 두 가지 의사결정을 동시에 결정하여야 하는 매우 복잡한 문제이다. 또한 파장할당시에 동일한 링크를 공유하는 광경로에는 동일한 파장을 할당할 수 없다는 제악이 있으면서, 목적함수는 할당하는 파장의 수를 죄소화하는 것이 된다. 본 연구에서는 링 루팅 및 파장할당 문제에 대매 평행루팅을 만족하는 최적해가 항상 존재한다는 것을 보이고, 최적해의 다양한 특성들을 규명하기로 한다. 또한 새로운 하한을 제시하고 이 하한이 기존의 하한에 비해서 매우 효과적임을 보이도록 한다.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.111-118
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• 2015

This paper deals with the routing and wavelength assignment problem (RWAP) that decides the best lightpaths for multiple packet demands for (s,t) in optical communication and assigns the minimum number of wavelengths to given lightpaths. There has been unknown of polynomial-time algorithm to obtain the optimal solution for RWAP. Hence, the RWAP is classified as NP-complete problem and one can obtain the approximate solution in polynomial-time. This paper decides the shortest main and alternate lightpath with same hop count for all (s,t) for given network in advance. When the actual demands of communication for particular multiple packet for (s,t), we decrease the maximum utilized edge into b utilized number using these dual-paths. Then, we put these (s,t) into b-wavelength bins without duplicated edge. This algorithm can be get the optimal solution within O(kn) computational complexity. For two experimental data, the proposed algorithm shows that can be obtain the known optimal solution.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.823-828
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• 2005

Ant Colony System (ACS) applied to the traveling salesman problem (TSP) has demonstrated a good performance on the small TSP. However, in case of the large TSP. ACS does not yield the optimum solution. In order to overcome the drawback of the An for the large TSP, the present study employs the idea of subpath to give more irormation to ants by computing the distance of subpath with length u. in dealing with the large TSP, the experimental results indicate that the proposed algorithm gives the solution much closer to the optimal solution than does the original ACS. In comparison with the original ACS, the present algorithm has substantially improved the performance. By utilizing the proposed algorithm, the solution performance has been enhanced up to $70\%$ for some graphs and around at $30\%$ for averaging over all graphs.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.06a
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• pp.167-175
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• 2003

본 연구는 (s, S) 재고시스템의 최적 재고정책을 수립하는 문제를 시뮬레이션을 통하여 분석하고자 한다. 이러한 목적으로 재고관리비용에 대한 파라미터 (s, S)의 민감도를 퍼터베이션 분석법으로 구하고 확률 최적화 기법을 적용하여 단위 기간에 평균 재고관리비용을 최적으로 하는 재고정책을 발견하였다. 민감도의 추정에는 IPA법과 SPA법을 표본경로의 주문 사건 변동에 따라 조건적으로 결합하여 사용하였다. 시뮬레이션 결과 s와 S의 최적정책 추정치를 상당히 정확한 값으로 얻었으며 이러한 결과는 보다 일반적인 재고관리 문제의 분석에 도움을 줄 것으로 기대한다.