• Journal of the Korean Operations Research and Management Science Society
• /
• v.18 no.2
• /
• pp.105-130
• /
• 1993

This study deals with finding a schedule for the movement of a material handling device (elevator) in a manufacturing plant. Two different algorithm (Traveling Salesman Technique and Greedy Algorithm) are used in the scheduling of the elevators using a simulation technique to determine the proper method of scheduling the elevator movement. Based on the simulation analysis, we have found that the Greedy algorithm serves better than the algorithm based on Traveling Salesman technique for scheduling the movement of a material handling device in the manufacturing plant.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2000.10a
• /
• pp.321-324
• /
• 2000

조합 최적화 문제인 Traveling Salesman problems(TSP)을 Genetic Algorithm(GA)[3]과 Local Search Heuristic Algorithm[8]을 이용하여 접근하는 것은 최적해를 구하기 위해 널리 알려진 방법이다. 본 논문에서는 TSP문제를 해결하기 위한 또 다른 접근법으로, 다수의 Ant들이 Tour들을 찾는 ACS(Ant Colony System) Algorithms[4][6][7]을 소개하고, ACS에서 Global Optima를 찾는 과정에서, 이미 이루어져 있는 Ant들의 Tour결과들을 서로 비교한다. Global Updating Rule에 의해 Global Best Tour 에 속해 있는 각 Ant Tour의 edge들을 update하는 ACS Algorithm에, 각 루프마다 Ant Tour들을 우성과 열성 인자들로 구분하고, 각각의 우성과 열성 인자들에 대해서 Global Updating Rule에 기반한 가중치를 적용(Weight Updating Rule)하므로서 기존의 ACS Algorithm보다 효율적으로 최적 해를 찾아내는 방법에 대해서 논하고자 한다.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.42 no.3
• /
• pp.1-7
• /
• 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.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.33 no.2
• /
• pp.17-26
• /
• 2008

The traveling salesman problem is to find tours through all cities at minimum cost ; simply visiting the cities only once that a salesman wants to visit. As such, the traveling salesman problem is a NP-complete problem ; an heuristic algorithm is preferred to an exact algorithm. In this paper, we suggest an effective cost relaxation using a candidate arc set which is obtained from a regression function for the traveling salesman problem. The proposed method sufficiently consider the characteristics of cost of arcs compared to existing methods that randomly choose the arcs for relaxation. For test beds, we used 31 instances over 100 cities existing from TSPLIB and randomly generated 100 instances from well-known instance generators. For almost every instances, the proposed method has found efficiently better solutions than the existing method.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.17 no.11
• /
• pp.2655-2663
• /
• 1993

In order to evaluate the relative significance of tolerance management of various elements in a VHS VTR tape transport system, the effect of geometric variations of the elements from standard design values on the tape traveling path is studied. The tape is modeled as a string and each element in the tape transport system is modeled as a cylinder whose radius, position vector and orientation vector are specified. An numerical algorithm is proposed to find the coordinates of tape entry points and tape exit points for the elements from which the tape traveling path can be completely described. By using the suggested algorithm, an error sensitivity analysis of tape traveling path due to the geometric variations of tape transport elements is performed for a particular model in the market and the elements demanding relatively strict tolerance management are identified.

• IE interfaces
• /
• v.24 no.1
• /
• pp.51-57
• /
• 2011

The traveling purchaser problem (TPP) is a generalization of the well-known traveling salesman problem (TSP), which has many real-world applications such as purchasing the required raw materials for the manufacturing factories and the scheduling of a set of jobs over some machines, and many others. In the last decade, TPP has received some attention of the researchers in the operational research area. However, all of the past researches for TPP are restricted on a single purchaser (vehicle). It could be the limitation to solve the real world problem. The purpose of this paper is to suggest the capacitated multiple TPP (CMTPP). It could be used in inbound logistics optimization in supply chain management area and many others. Since TPP is known as NP-hard, we also developed the heuristic algorithm to solve the CMTPP.

• Proceedings of the Korean Information Science Society Conference
• /
• 1999.10b
• /
• pp.9-11
• /
• 1999

조합 최적화 문제인 Traveling Salesman problems(TSP)을 Genetic Algorithm(GA)과 Local Search Heuristic인 Lin-Kernighan(LK) Heuristic[2]을 이용하여 접근하는 것은 최적해를 구하기 위해 널리 알려진 방법이다. 이 논문에서는 LK를 이용하여 주어진 TSP 문제에서 Local Optima를 찾고, GA를 이용하여 Local Optimal를 바탕으로 Global Optima를 찾는데 이용하게 된다. 여기서 이런 GA와 LK를 이용하여 TSP 문제를 풀 경우 해가 점점 수렴해가면서 중복된 유전자가 많이 생성된다. 이런 중복된 유전자를 제거함으로써 탐색의 범위를 보다 넓고 다양하게 검색하고, 더욱 효율적으로 최적화를 찾아내는 방법에 대해서 논하겠다. 이런 방법을 이용하여 rat195, gil262, lin318의 TSP문제에서 효율적으로 수행된다.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.30 no.2
• /
• pp.157-167
• /
• 2005

This paper presents a new perturbation technique for developing efficient iterated local search procedures for the asymmetric traveling salesman problem(ATSP). This perturbation technique uses global information on ATSP instances to speed-up computation and to improve the quality of the tours found by heuristic method. The main idea is to escape from a local optima by introducing perturbations on the out-of-kilter arcs in the problem instance. For a local search heuristic, we use the Kwon which finds optimum or near-optimum solutions by applying the out-of-kilter algorithm to the ATSP. The performance of our algorithm has been tested and compared with known method perturbing on randomly chosen arcs. A number of experiments has been executed both on the well-known TSPLIB instances for which the optimal tour length is known, and on randomly generated Instances. for 27 TSPLIB instances, the presented algorithm has found optimal tours on all instances. And it has effectively found tours near AP lower bound on randomly generated instances.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.10a
• /
• pp.783-786
• /
• 2008

외판원문제(Traveling Salesman problem: TSP)는 전형적인 조합최적화 문제로 위치하는 n개의 모든 지점을 오직 한번씩만 방문하는 순회경로를 결정하는 과정에서 순회비용 또는 순회거리를 최소화한다. 따라서 본 논문에서는 종래의 NP-hard문제로 널리 알려진 TSP를 해결하기 위해서 메타 휴리스틱기법 중에서 가장 널리 이용되고 있는 유전 알고리즘(Genetic Algorithm: GA)을 이용한다. 마지막으로, 유전 알고리즘을 이용해 외판원문제에 적합한 성능을 보이는 유전 연산자를 찾아내기 위해 수치 실험을 통해 그 성능에 대한 평가를 한다.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.22 no.52
• /
• pp.97-107
• /
• 1999

The asymmetric traveling salesman problem is a representative NP-Complete problem. Polynomial algorithm for this problem has not been yet found. So, many heuristic methods have been researched in this problem. We need heuristic methods that produce good answers for some larger problems in reasonable times. 3-opt is well known for the effective local-search heuristic method. It has been used in many applications of the asymmetric traveling salesman problem. This paper discusses 3-opt's properties and ineffective aspects and presents a highly effective heuristic method. 3-opt does not consider good arcs(shorter distance or little cost). This paper presents a fast heuritic algorithm compared with 3-opt by inserting good arcs and deleting related arcs later.