• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.04a
• /
• pp.1354-1356
• /
• 2012

최근 ITS(Intelligent Transportation Systems)의 개발과 함께 차량용 내비게이션의 사용이 급증하면서 경로탐색의 중요성이 더욱 가속화되고 있다. 현재 차량용 내비게이션은 멀티미디어 및 정보통신 기술의 결합과 함께 다양한 기능 및 정보를 사용자에게 제공하고 있으며 이러한 기능과 정보를 사용해서 목적지점까지의 최단경로를 탐색하는 것이 내비게이션 시스템의 핵심기능이다. 이러한 경로탐색 알고리즘은 교통시스템, 통신 네트워크, 운송 시스템은 물론 이동 로봇의 경로 설정 등 다양한 분야에 사용되고 있다. 개미 집단 최적화(Ant Colony Optimization, ACO) 알고리즘은 메타 휴리스틱 탐색 방법으로 그리디 탐색(Greedy Search)뿐만 아니라 긍정적 반응의 탐색을 사용한 모집단에 근거한 접근법으로 순환 판매원 문제(Traveling Salesman Problem, TSP)를 풀기 위해 처음으로 제안되었다. 본 논문에서는 개미 집단 최적화(ACO) 알고리즘이 기존의 경로 탐색 알고리즘으로 알려진 Dijkstra 보다 최단경로 탐색에 있어서 더 적합한 알고리즘이라는 것을 설명하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.01a
• /
• pp.39-40
• /
• 2019

본 논문에서는 연관규칙 마이닝 알고리즘인 Apriori 알고리즘을 기반으로 향상된 인공벌 군집 알고리즘(ABC algorihtm)을 적용하여 SDN 환경에서 분산된 컨트롤러를 선택하는 모델을 제안하였다. 이를 통해 자주 사용되는 컨트롤러를 우선적으로 선택함으로써 향상된 컨트롤러 선택을 목표로 한다.

• Journal of Korean Association for Spatial Structures
• /
• v.21 no.2
• /
• pp.89-97
• /
• 2021

This paper describes an adaptive hybrid evolutionary firefly algorithm for a topology optimization of truss structures. The truss topology optimization problems begins with a ground structure which is composed of all possible nodes and members. The optimization process aims to find the optimum layout of the truss members. The hybrid metaheuristics are then used to minimize the objective functions subjected to static or dynamic constraints. Several numerical examples are examined for the validity of the present method. The performance results are compared with those of other metaheuristic algorithms.

• Journal of ILASS-Korea
• /
• v.28 no.4
• /
• pp.161-168
• /
• 2023

Droplet impingement on solid surfaces is pivotal for a range of spray and heat transfer processes. This study aims to optimize the cooling performance of single droplet impingement on heated textured surfaces. We focused on maximizing the cooling effectiveness or the total contact area at the droplet maximum spread. For efficient estimation of the optimal values of the unknown variables, we introduced an enhanced Genetic Algorithm (GA) and Particle swarm optimization algorithm (PSO). These novel algorithms incorporate its developed theoretical backgrounds to compare proper optimized results. The comparison, considering the peak values of objective functions, computation durations, and the count of penalty particles, confirmed that PSO method offers swifter and more efficient searches, compared to GA algorithm, contributing finding the effective way for the spray and droplet impingement process.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.9
• /
• pp.161-168
• /
• 2014

The optimal solution of minimum cost for aircraft landing problem(ALP) is very difficult problem because the approached aircraft are random time interval. Therefore this problem has been applied by various meta heuristic methods. This paper suggests O(nlog n) polynomial time heuristic algorithm to obtain the optimal solution for ALP. This algorithm sorts the target time of aircraft into ascending order. Then we apply the optimization of change the landing sequence take account of separation time and the cost of landing. For the Airland1 through Airland8 of benchmark data of ALP, we choose 25 data until the number of runway m that the total landing cost is 0. We can be obtain the optimal solution for all of the 25 data. Especially we can be improve the known optimal solution for m = 1of Airland8.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.2
• /
• pp.209-214
• /
• 2020

The equitable partitioning problem(EPP) is classified as [0/1] binary skill existence or nonexistence and integer skill levels such as [1,2,3,4,5]. There is well-known a polynomial-time optimal solution finding algorithm for binary skill EPP. On the other hand, tabu search a kind of metaheuristic has apply to integer skill level EPP is due to unknown polynomial-time algorithm for it and this problem is NP-hard. This paper suggests heuristic greedy algorithm with polynomial-time to find the optimal solution for integer skill level EPP. This algorithm descending sorts of skill level frequency for each field and decides the lower bound(LB) that more than the number of group, packing for each group bins first, than the students with less than LB allocates to each bin additionally. As a result of experimental data, this algorithm shows performance improvement than the result of tabu search.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.10a
• /
• pp.479-482
• /
• 2011

This paper proposes a design of a ship backbone network-based on the survival and efficiency of the ship network. Currently IEC operates the standard ship network, a standard specification "IEC 61162-410 maintains the operation of the network. IEC 61162-410 offers a high stability of the ship network by using terminal equipment. But current studies are incomplete because it has been assumed that the ship's network will operate at double its current capacity. This paper analyzes the double ship backbone topology for an organization and then will summarise the minimum costs required to implement the ship backbone topology using an ILP. Also, we present an effective traffic assignment technique that uses an ILP, metaheuristic, heuristic algorism-based underlying the ship backbone network. The results by experimenting the design of the network confirmed a greter efficiency, stability and cost-effectiveness of the ship network.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.2
• /
• pp.89-96
• /
• 2022

This paper suggests heuristic algorithm for single-model cross-over assembly line balancing problem that is a kind of NP-hard problem. The assembly line balance problem is mainly applied with metaheuristic methods, and no algorithm has been proposed to find the exact solution of polynomial time, making it very difficult to apply in practice. The proposed bi-directional clustering algorithm computes the minimum number of worker m^* = ⌈W/c⌉ and goal cycle time c^* = ⌈W/m^*⌉ from the given total assembling time W and cycle time c. Then we assign each workstation i=1,2,…,m^* to T_i=c^* ±α≤ c using bi-directional clustering method. For 7 experimental data, this bi-directional clustering algorithm same performance as other methods.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.9
• /
• pp.69-76
• /
• 2022

The traveling salesman problem(TSP) is one of the most famous combinatorial optimization problem. So far, many metaheuristic search algorithms have been proposed to solve the problem, and one of them is local search. One of the very important factors in local search is neighbor generation method, and random-based neighbor generation methods such as inversion have been mainly used. This paper proposes 4 new greedy-based neighbor generation methods. Three of them are based on greedy insertion heuristic which insert selected cities one by one into the current best position. The other one is based on greedy rotation. The proposed methods are applied to first-choice hill-climbing search and simulated annealing which are representative local search algorithms. Through the experiment, we confirmed that the proposed greedy-based methods outperform the existing random-based methods. In addition, we confirmed that some greedy-based methods are superior to the existing local search methods.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.7
• /
• pp.29-37
• /
• 2020

In the past, meta-heuristic optimization algorithms were developed to solve the problems caused by complex nonlinearities occurring in natural phenomena, and various studies have been conducted to examine the applicability of the developed algorithms. The self-adaptive vision correction algorithm (SAVCA) showed excellent performance in mathematics problems, but it did not apply to complex engineering problems. Therefore, it is necessary to review the application process of the SAVCA. The SAVCA, which was recently developed and showed excellent performance, was applied to the advanced Muskingum flood routing model (ANLMM-L) to examine the application and application process. First, initial solutions were generated by the SAVCA, and the fitness was then calculated by ANLMM-L. The new value selected by a local and global search was put into the SAVCA. A new solution was generated, and ANLMM-L was applied again to calculate the fitness. The final calculation was conducted by comparing and improving the results of the new solution and existing solutions. The sum of squares (SSQ) was used to calculate the error between the observed and calculated runoff, and the applied results were compared with the current models. SAVCA, which showed excellent performance in the Muskingum flood routing model, is expected to show excellent performance in a range of engineering problems.