• IE interfaces
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• v.23 no.2
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• pp.139-146
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• 2010

In this paper, we present the study of a real passenger transportation system. Passenger transportation problem aims to transport passengers from bus stops to their destinations by a fleet of vehicles while satisfying various constraints such as vehicle capacity, maximum allowable riding time in a bus, and time windows at destinations. Our problem also has special issues such as mixed loading, consideration of afternoon problem together with morning problem, and transferring passengers between vehicles. Our solution approach consists of three serial procedures: bus route generation, bus scheduling, and post optimization. Efficient heuristic algorithms were developed and implemented for the procedures. The proposed solution approach has been successfully applied to several real world problem instances and could reduce about 10% to 15% of buses.

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.93-113
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• 2007

In the previous research, we considered a logistics brokerage problem with the objective of minimizing total transportation lead time of freights in a logistics e-marketplace, in which a logistics brokerage agent intermediates empty vehicles and freights registered by car owners and shippers [7]. However, in the logistics e-marketplace, transportation due date tardiness is more important than the transportation lead time, since transportation service level is critically determined by whether the due date is met or not. Therefore, in this paper, we deal with the logistics brokerage problem with the objective of minimizing total tardiness of freights. Hungarian method based matching algorithms, real time matching(RTM), periodic matching(PM), and fixed matching(FM), are used for solving the problem considered in this paper. In order to test performance of the proposed algorithms, we perform computational experiments on a various problem instances. The results show that the waiting-and-matching algorithms, PM and FM, also give better performance than real time matching strategy, RTM, for the total tardiness minimization problem as the algorithms did for the total lead time minimization problem.

• Journal of Distribution Science
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• v.14 no.2
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• pp.41-45
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• 2016

Purpose - Finding an optimal path is an essential component for the design and operation of smart transportation or logistics network. Many applications in navigation system assume that travel time of each link is fixed and same. However, in practice, the travel time of each link changes over time. In this paper, we introduce a new transportation problem to find a latest departing time and delivery path between the two nodes, while not violating the appointed time at the destination node. Research design, data, and methodology - To solve the problem, we suggest a mathematical model based on network optimization theory and a backward search method to find an optimal solution. Results - First, we introduce a dynamic transportation problem which is different with traditional shortest path or minimum cost path. Second, we propose an algorithm solution based on backward search to solve the problem in a large-sized network. Conclusions - We proposed a new transportation problem which is different with traditional shortest path or minimum cost path. We analyzed the problem under the conditions that travel time is changing, and proposed an algorithm to solve them. Extending our models for visiting two or more destinations is one of the further research topics.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.449-460
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• 2007

Several fuzzy approaches can be considered for solving multi-objective transportation problem. This paper presents a fuzzy goal programming approach to determine an optimal compromise solution for the multiobjective transportation problem. We assume that each objective function has a fuzzy goal. Also we assign a special type of nonlinear (hyperbolic) membership function to each objective function to describe each fuzzy goal. The approach focuses on minimizing the negative deviation variables from 1 to obtain a compromise solution of the multiobjective transportation problem. We show that the proposed method and the fuzzy programming method are equivalent. In addition, the proposed approach can be applied to solve other multiobjective mathematical programming problems. A numerical example is given to illustrate the efficiency of the proposed approach.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.79-86
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• 2005

The transportation problem (TP) is one of the traditional optimization problems. Unlike the TP, the fixed charge transportation problem (FCTP) cannot be solved using polynomial time algorithms. So, finding solutions for the FCTP is a well-known NP-complete problem involving an importance in a transportation network design. So, it seems to be natural to use evolutionary algorithms for solving FCTP. And many evolutionary algorithms have tackled this problem and shown good performance. This paper introduces an efficient evolutionary algorithm for the FCTP. The proposed algorithm can always generate feasible solutions without any repair process using the random key representation. Especially, it can guide the search toward the basic solution. Finally, we performed comparisons with the previous results known on the benchmark instances and could confirm the superiority of the proposed algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.10a
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• pp.36-48
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• 1994

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.195-204
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• 2003

Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.

• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.2
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• pp.55-69
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• 2022

Purpose - This study is a study to investigate the problem of the selection of means of transportation in international logistics by studying the basics of logistics activities, selection factors of transportation methods, and multimodal transportation. Research design, data, methodology - This study is composed of 5 chapters through literature study. Chapter 1 describes the functions and transportation system of international logistics, Chapter 2 selects transportation, Chapter 3 deals with maritime transportation and multimodal transportation, Chapter 4 describes multimodal transportation in terms of customer service, Chapter 5 addresses the implications and conclusions. Results - When looking at the problem of selecting a means of transportation, it is important that the parties involved in the transportation choose which means of transportation for their convenience and profit during the transportation process. Here, there will be factors to consider, including transportation cost, when selecting a means of transportation, and each means of transportation may have characteristics or advantages and disadvantages. Considering all these points, the adoption of multimodal transportation from a customer service point of view may be the answer. Conclusions - This study pays attention to the academic understanding related to the selection of means of transportation and to how usefully this thesis can be used in the selection of transportation related persons, especially shippers, from a practical level.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.223-230
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• 2015

As the Transportation Simplex Method of the general transportation problem are inapplicable to the large-scale unbalanced transportation problem, a commercialized linear programming package remains as the only viable means. There is, however, no method made available to verify the optimality of solutions attained by the package. This paper therefore proposes a simple heuristic algorithm to the large-scale unbalanced transportation problem. From a given problem of $31{\times}15$supply and demand areas, the proposed algorithm determines the number of demands areas for each supply area and executes on the latter in the ascending order of each of their corresponding demand areas. Next, given a single corresponding demand area, it supplies the full demand volume and else, it supplies first to an area of minimum associated costs and subsequently to the rest so as to meet the demand to the fullest extent. This initial optimal value is then optimized through an adjustment process whereby costs are minimized as much as possible. When tested on the $31{\times}15$cost matrix, the proposed algorithm has obtained an optimal result improved from the commercial linear programming package by 8.9%.

• Journal of Korean Society of Transportation
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• v.5 no.1
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• pp.47-58
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• 1987

A commodity distribution problem with intertemporal storage facilities and dynamic transportation networks is proposed. mathematical integer programming methods and multiobjective programming techniques are used in the model formulation. Dynamic characteristics of commodity distribution problems are taken into account in the model formulation. storage facility location problems and transportation link addition problems are incorporated into the intertemporal multicommodity distribution problem. The model is capable of generating the most efficient and rational commodity distribution system. Therefore it can be utilized to provided the most effective investment plan for the transportation infrastructure development as well as to evaluate the existing commodity distribution system. The model determines simultaneously the most efficient locations, sizes, and activity levels of storage facilities as well as new highway links. It is extended to multiobjective planning situations for the purpose of generating alternative investment plans in accordance to planning situations. sine the investment in transportation network improvement yields w\several external benefits for a regional economy, the induced benefit maximization objective is incorporated into the cost minimization objective. The multiobjective model generates explicitly the trade-off between cost savings and induced benefits of the investment in transportation network improvement.