• Industrial Engineering and Management Systems
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• 제12권2호
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• pp.161-170
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• 2013

Deployment of green transportation in reverse logistics is a key issue for low carbon technologies. To cope with such logistic innovation, this paper proposes a hybrid approach to solve practical vehicle routing problem (VRP) of pickup type that is common when considering the reverse logistics. Noticing that transportation cost depends not only on distance traveled but also on weight loaded, we propose a hierarchical procedure that can design an economically efficient reverse logistics network even when the scale of the problem becomes very large. Since environmental concerns are of growing importance in the reverse logistics field, we need to reveal some prospects that can reduce $CO_2$ emissions from the economically optimized VRP in the same framework. In order to cope with manifold circumstances, the above idea has been deployed by extending the Weber model to the generalized Weber model and to the case with an intermediate destination. Numerical experiments are carried out to validate the effectiveness of the proposed approach and to explore the prospects for future green reverse logistics.

• Korean Journal of Mathematics
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• 제4권1호
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• pp.7-16
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• 1996

The optimization problems with quadratic constraints often appear in various fields such as network flows and computer tomography. In this paper, we propose an algorithm for solving those problems and prove the convergence of the proposed algorithm.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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• pp.793-796
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• 2008

본 논문은 생산 물류 시스템최적화의 실현에 가장 대표적인 생산수송계획문제인 수송문제(TP: Transportation Problem)에 고정비용을 고려한 고정비용 수송문제(fcTP: Fixed charge Transportation Problem)를 다룬다. 특히 NP-hard문제로 널리 알려진 TP에서 수송량에 비례하는 가변비용과 함께 추가적으로 모든 경로에서 발생하는 고정비용을 함께 고려한 fcTP를 다룬다. 따라서 이러한 fcTP를 해결하기 위해 메타 휴리스틱기법 중에 가장 널리 이용되고 있는 유전 알고리즘(CA: Genetic Algorithm)을 이용한 해법을 제시하고자 한다. 본 논문에서는 CA를 이용해 고정비용 수송문제의 해를 우선순위기반 유전자 표현법을 이용해 fcTP에 적용해 보고 수치 실험을 통해 그 성능에 대한 연구를 한다.

• 한국경영과학회지
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• 제41권4호
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• pp.113-128
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• 2016

This paper proposes a Bi-level Genetic Algorithm for the Fixed Charge Transportation Problem with Non-linear Unit Cost. The problem has the property of mixed integer program with non-linear objective function and linear constraints. The bi-level procedure consists of the upper-GA and the lower-GA. While the upper-GA optimize the connectivity between each supply and demand pair, the lower-GA optimize the amount of transportation between the pairs set to be connected by the upper-GA. In the upper-GA, the feasibility of the connectivity are verified, and if a connectivity is not feasible, it is modified so as to be feasible. In the lower-GA, a simple method is used to obtain a pivot feasible solution under the restriction of the connectivity determined by the upper-GA. The obtained pivot feasible solution is utilized to generate the initial generation of chromosomes. The computational experiment is performed on the selected problems with several non-linear objective functions. The performance of the proposed procedure is analyzed with the result of experiment.

• 한국경영과학회지
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• 제32권3호
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• pp.63-80
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• 2007

This study is a generalization of 'stable dynamics' recently suggested by Nesterov and de Palma[29]. Stable dynamics is a new model which describes and provides a stable state of congestion in urban transportation networks. In comparison with user equilibrium model that is common in analyzing transportation networks, stable dynamics requires few parameters and is coincident with intuitions and observations on the congestion. Therefore it is expected to be an useful analysis tool for transportation planners. An equilibrium in stable dynamics needs only maximum flow in each arc and Wardrop[33] Principle. In this study, we generalize the stable dynamics into the model with multiple traffic classes. We classify the traffic into the types of vehicle such as cars, buses and trucks. Driving behaviors classified by age, sex and income-level can also be classes. We develop an equilibrium with multiple traffic classes. We can find the equilibrium by solving the well-known network problem, multicommodity minimum cost network flow problem.

• Geomechanics and Engineering
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• 제17권3호
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• pp.227-236
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• 2019

In practice, the natural slopes are frequently with soils of spatial properties and irregular features. The traditional limit analysis method meets an inherent difficulty to deal with the stability problem for such slopes due to the normal condition in the associated flow rule. To overcome the problem, a novel technique based on the upper bound limit analysis, which is called the discretization technique, is employed for the stability evaluation of complex slopes. In this paper, the discretization mechanism for complex slopes was presented, and the safety factors of several examples were calculated. The good agreement between the discretization-based and previous results shows the accuracy of the proposed mechanism, proving that it can be an alternative and reliable approach for complex slope stability analysis.

• 교통기술과정책
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• 제8권4호
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• pp.55-59
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• 2011

• 교통기술과정책
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• 제9권4호
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• pp.13-16
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• 2012

• 한국경영과학회지
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• 제16권2호
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• pp.86-102
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• 1991

The purpose of this paper is to present a branch and bound algorithm for the hierarchical transportation network design problem in 2-level directed networks. This problem is to find the least cost of hierarchical transportation networks which consist of a primary path and a secondary path. The primary path is a simple path from a prespecified orgin node to a prespecified terminal node. All nodes must be either a transsipment node on the primary path or connected to that path via secondary arcs. This problem is formulated to a 0-1 inter programming problem with assignment and illegal subtour elimination equations as constaints. We show that the subproblem relaxing subtour elimination constraints is transformed to a linear programming problem by means of the totally unimodularity. Optimal solutions of this subproblem are polynoially obtained by the assignment algorithm and complementary slackness conditions. Therefore, the optimal value of this subproblme is used as a lower bound. When an optimal solution of the subproblem has an illegal subtour, a better disjoint rule is adopted as the branching strategy for reducing the number of branched problems. The computational comparison between the least bound rule and the depth first rule for the search strategy is given.

• 한국경영과학회지
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• 제31권2호
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• pp.141-155
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• 2006

In this paper, we address an extended hub-and-spoke transportation network design problem (EHSNP). In the existing hub location problems, the location and number of spokes, and shipments on spokes are given as input data. These may, however, be viewed as the variables according to the areas which they cover. Also, the vehicle routing in each spoke needs to be considered to estimate the network cost more correctly. The EHSNP is a problem of finding the location of hubs and spokes, and pickup/delivery routes from each spoke, while minimizing the total related transportation cost in the network. The EHSNP is an integrated problem that consists of several interrelated sub-problems. To solve EHSNP, we present an approach based on a symbiotic evolutionary algorithm (symbiotic EA), which are known as an efficient tool to solve complex integrated optimization problems. First, we propose a framework of symbiotic EA for EHSNP and its genetic elements suitable for each sub-problem. To analyze the proposed algorithm, the extensive experiments are performed with various test-bed problems. The results show that the proposed algorithm is promising in solving the EHSNP.