• Industrial Engineering and Management Systems
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• v.13 no.2
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• pp.163-171
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• 2014

Under amazing increase in markets and certain demand on qualified service in the delivery system, global logistic optimization is becoming a keen interest to provide an essential infrastructure coping with modern competitive prospects. As a key technology for such deployment, we have been engaged in the practical studies on vehicle routing problem (VRP) in terms of Weber model, and developed a hybrid approach of meta-heuristic methods and the graph algorithm of minimum cost flow problem. This paper extends such idea to multi-depot VRP so that we can give a more general framework available for various real world applications including those in green or low carbon logistics. We show the developed procedure can handle various types of problem, i.e., delivery, direct pickup, and drop by pickup problems in a common framework. Numerical experiments have been carried out to validate the effectiveness of the proposed method. Moreover, to enhance usability of the method, Google Maps API is applied to retrieve real distance data and visualize the numerical result on the map.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.285-288
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• 2000

본 연구는 Heuristic 알고리즘 및 유전자알고리즘(GA)을 이용하여 수거(Pickup) 및 배달(Delivery)을 동시에 고려한 통합차량운송계획 모델의 개발이다. 본 연구는 기존의 TSP의 문제를 확장 응용하였으며, 이는 한 Route에서 수거지(Origin)와 운반지(Destination)를 포함하는 수요들을 만족하도록 운반되어야 하는 문제이다. 이러한 통합차량경로계획문제(VRP Vehicle Routing Problem)를 해결하기 위한 접근방법으로 Heuristic 방법을 사용하였으며, 기존의 Saving 알고리즘과 유전자알고리즘(Genetic Algorithm)의 각종 연산자(Operators)들을 계산하여 사용한 TSP문제의 해를 본 연구의 해의 초기해로 사용하였으며 수거 및 배달문제의 특성을 고려하여 해를 구하였다. 본 연구의 결과를 다양한 운송환경에서, 거리산정방법, 가용운송장비 대수, 운송시간의 제한, 물류센터 및 운송지점의 위치 및 수요량 등 다양한 인자들을 고려한 통합시스템으로 프로그램을 개발하고 Sample 문제를 통하여 응용결과를 보였다.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.114-120
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• 1999

본 연구는 Heuristic 알고리즘 및 유전자알고리즘(GA)을 이용하여 3단계의 통합차량운송계획 모델의 개발이다. 차량경로문제(VRP : Vehicle Routing Problem)를 해결하기 위한 접근방법으로 기존의 Saving 알고리즘을 개선하여 사용하였으며 유전자 알고리즘(Genetic Algorithm)의 각종 연산자 (Operators)들을 계산하여 사용하였다. 본 모델은 다음 3단계의 접근방법을 사용하였다 ; 1) 다 물류 센터의 문제해결을 위한 영역활당(Sector Clustering) 모델, 2) 경로계획모델(VRP Model), 및 3) 최적 운송계획모델(GA-TSP Model). 본 모델들을 다양한 운송환경에서, 거리산정방법, 가용운송장비 대수, 운송시간의 제한, 물류센터 및 운송지점의 위치 및 수요량 등 다양한 파라메터들을 고려한 통합시스템으로 3개의 Component로 구성된 GUI-Type 프로그램을 개발하고 Sample 응용결과를 보였으며 기존의 모델들 보다 우수한 결과를 보였다.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.441-451
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• 2014

This article addresses an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using the artificial bee colony algorithm. The objective function is adapted to enhance the overall system static voltage stability index and to achieve maximum net yearly savings. Load variations have been considered to optimally scope the fixed and switched capacitors required. The numerical results are compared with those obtained using recent heuristic methods and show that the proposed approach is capable of generating high-grade solutions and validated viability.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.153-165
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• 2009

This paper apollos an ant colony system (ACS) for the vehicle routing problem with time window (VRPTW). The VRPTW is a generalization of the VRP where the service of a customer can begin within the time windows defined by the earliest and latest times when the customer will permit the start of service. The ACS has been applied effectively in geographical environment such as TSP or VRP by meta-heuristic that imitate an ant's biologic special duality in route construction, 3 saving based ACS (SB-ACS) is introduced and its solution is improved by local search. Through iterative precesses, the SB-ACS is shown to drive the best solution. The algorithm has been tested on 56 Solomon benchmarking problems and compared to the best-known solutions on literature. Experimental results shows that SB-ACS algorithm could obtain food solution in total travel distance minimization.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.65
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• pp.81-88
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• 2001

In logistics decision making, Key elements in the design of any physical distribution are the location of depots and the distribution of goods from the depots to the customers. Considering open and close the depots, This paper presents a flexible analysis on the combined location-routing problem(LRP) the case for variation capacity of vehicle and customers demands each. The scenario examples are given the use of heuristic(Saving-Drop) in LRP types. The results is useful in apply to the logistics environment changes.

• The KIPS Transactions:PartA
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• v.14A no.5
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• pp.317-326
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• 2007

We propose more enhanced heuristic for the GOSST(Grade of Services Steiner Minimum Tree) problem in this paper. GOSST problem is a variation of Steiner Tree problem and to find a network topology satisfying the G-Condition with minimum network construction cost. GOSST problem is known as one of NP-Hard or NP-Complete problems. In previous our research, we proposed a heuristic employing Direct Steiner Point Locating strategy with Distance Preferring MST building strategy. In this paper, we propose new Steiner point locating strategy, Zigzag Steiner point Locating strategy. Through the results of out experiments, we can assert this strategy is better than our previous works. The Distance Zigzag GOSST method which hires the Distance Preferring MST building strategy and Zigzag Steiner point Locating strategy defrays the least network construction cost and brings 31.5% cost saving by comparison to G-MST, the experimental control and 2.2% enhancement by comparison to the Distance Direct GOSST method, the best GOSST method in our previous research.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.1
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• pp.8-16
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• 2013

We consider a problem of presort and loading of commercial bulk mails in a mailing service. Here, presort is the process by which a mailer prepares mail so that it is sorted to at least the finest extent required by the mailing service provider for the (discounted) price claimed. The problem is formulated as a special type of transportation problem. To solve industrial-sized problems, we develop an efficient heuristic algorithm and perform experimental tests on randomly generated problem instances. Results of the tests show that mailers can save mailing cost much more when they use small-sized mail trays with less frequent mailings. Also, large-sized mailers can obtain much more cost saving than small-sized mailers. In addition, cost saving effect is influenced by delivery area distribution of mails and fluctuation of mailing demand.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.673-678
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• 2007

본 연구는 지리학적으로 산재해 있는 다양한 수요지점을 서비스할 수 있는 차량경로모델을 개발한다. 즉 다양한 수요지점을 구역으로 분할하여 각 수요지점의 수요량과 서비스 레벨을 고려하여 최적차량 운송계획 모형을 개발하는 데 있다. 본 연구 방법에서 사용된 접근 방법으로 먼저 단일 출발점에서 각 수요지점의 수요조건을 만족하는 범위 내에서 최소의 운반 거리 및 수요 조건을 만족하도록 각 서비스 지역을 할당하는 Clustering Algorithm을 개발하여 단일 구역별 최적의 이동 경로를 개발하였다. 그리고 각 수요지점별 수요량의 평균과 표준편차를 고려하여 새로운 Saving Algorithm을 기반으로 하여 운송 가능한 차량별 수요지점을 할당하였다. 또한 각 차량경로 구역별 서비스 레벨을 고려한 개선된 알고리즘을 사용하여 차량경로 문제의 근본적인 목적인 이동 거리(비용, 시간)의 최소화와 고객서비스 극대화를 동시에 달성하기 위한 최적 차량 운송 계획 모델을 개발하였다. 마지막으로 수치적 예제를 통해 본 연구에서 사용된 모델들과 기존 모델들과의 비교를 수행하였다.

• Korean Management Science Review
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• v.15 no.2
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• pp.201-210
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• 1998

Truck dispatching is one of the most commonly occurring problems of transprot management. We developed an interactive decision support system named IDSSTD, for the truck dispatching problem where two conflicting objectives are treated and travel speed varies depending on the passing areas and time of day. The IDSSTD aids the decision-making process by allowing the user to interact directly with the database, to direct data to a decision model, and to portray results in a convenient form. The IDSSTD is consisted of two major interactive phases. The pre-scheduling interactive phase is to reduce the complexity of a given problem before applying the BC-saving heuristic algorithm and the post-scheduling interactive phase is to improve practically the algorithmic solution. The IDSSTD has the capabilities of its own manipulation(analysis and recommendation) and diverse graphic features in order to facilitate a user's interaction.