• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.16-22
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• 2019

After Dantzig and Rasmer introduced Vehicle Routing Problem in 1959, this field has been studied with numerous approaches so far. Classical Vehicle Routing Problem can be described as a problem of multiple number of homogeneous vehicles sharing a same starting node and having their own routes to meet the needs of demand nodes. After satisfying all the needs, they go back to the starting node. In order to apply the real world problem, this problem had been developed with additional constraints and pick up & delivery model is one of them. To enhance the effectiveness of pick up & delivery, hub became a popular concept, which often helps reducing the overall cost and improving the quality of service. Lots of studies have suggested heuristic methods to realize this problem because it often becomes a NP-hard problem. However, because of this characteristic, there are not many studies solving this problem optimally. If the problem can be solved in polynomial time, optimal solution is the best option. Therefore, this study proposes a new mathematical model to solve this problem optimally, verified by a real world problem. The main improvements of this study compared to real world case are firstly, make drivers visit every nodes once except hub, secondly, make drivers visit every nodes at the right time, and thirdly, make drivers start and end their journey at their own homes.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.187-201
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• 1998

In ATM networks with high capacity, the effect of failures on transmission links or nodes can be catastrophic, so that the issue of survivability is of great importance. In this paper. we consider the routing problem for working and backup virtual paths(VPs). To accomplish a higher survivability. routing the two kinds of VPs should be taken into account at the same time because backup VP routing depends on the working VP routing. A coevolutionary algorithm is employed to solve the problem for simultaneously routing of working and backup VPs. To develop an efficient coevolutionary algorithm for the problem. structure of populations, encoding method, neighborhood, and genetic operators are studied in this paper. The results of extensive experiments are reported. The performance comparison of the proposed algorithm with a conventional genetic algorithm and existing heuristics shows that our approach is promising.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1731-1737
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• 2007

This paper considers subway routing problem. Given a schedule of train to be routed by a railway stock, the routing problem determines a sequence of trains while satisfying turnaround time and maintenance restrictions. Generally, the solution of routing problem is generated from set partition formulation solved by column generation method, a typical integer programming approach for train-set. However, we find the characteristics of metropolitan subway which has a simple rail network, a few end stations and 13 departure-arrival patterns. We reflect a turn-around constraint due to spatial limitations has no existence in conventional railroad. Our objective is to minimize the number of daily train-sets. In this paper, we develop two basic techniques that solve the subway routing problem in a reasonable time. In first stage, we formulate the routing problem as a Min-cost-flow problem. Then, in the second stage, we attempt to normalize the distance covered to each routes and reduce the travel distance using our heuristic approach. Applied to the current daily timetable, we could find the subway routings, which is an approximately 14% improvement on the number of train-sets reducing 15% of maximum traveling distance and 8% of the standard deviation.

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.1
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• pp.34-44
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• 1987

The general vehicle routing problem has been studied by many researchers such as Christofides, et al. and Laporte, et al., but only limited effort has been devoted to developing the optimal algorithms. The purpose of this paper is to develop a branch and bound algorithm which determines the optimal vechicle routes and the optimal number of vehicles concurrenetly for the asymmetrical vehicle routing problem. In order to enhance the efficiency, this algorithm emphasizes the followings ; First, an efficient primal-dual approach is developed to solve subproblems which are called the specialized transportation problem, formed by relaxing the illegal subtour constraints from the vehicle routing problem, second, an improved branching scheme is developed to reduce the number of candidate subproblems by adequate utilization of vehicle capacity restrictions.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.656-666
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• 2014

In delay tolerant networks (DTNs), delay is inevitable; thus, making better use of buffer space to maximize the packet delivery rate is more important than delay reduction. In DTNs, epidemic routing is a well-known routing protocol. However, epidemic routing is very sensitive to buffer size. Once the buffer size in nodes is insufficient, the performance of epidemic routing will be drastically reduced. In this paper, we propose a buffer scheme to optimize the performance of epidemic routing on the basis of the Lagrangian and dual problem models. By using the proposed optimal buffer scheme, the packet delivery rate in epidemic routing is considerably improved. Our simulation results show that epidemic routing with the proposed optimal buffer scheme outperforms the original epidemic routing in terms of packet delivery rate and average end-to-end delay. It is worth noting that the improved epidemic routing needs much less buffer size compared to that of the original epidemic routing for ensuring the same packet delivery rate. In particular, even though the buffer size is very small (e.g., 50), the packet delivery rate in epidemic routing with the proposed optimal buffer scheme is still 95.8%, which can satisfy general communication demand.

• Management Science and Financial Engineering
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• v.18 no.1
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• pp.27-37
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• 2012

This paper is motivated by a military cargo-plane routing problem which is a pickup-and-delivery problem in which load splits and node revisits are allowed (PDPLS). Although this recent evolution of a VRP-model enhances the efficiency of routing, a solution method is more of a challenge since the node revisits entail closed walks in modeling vehicle routes. For such a case, even a compact IP-formulation is not available and an effective method had been lacking until Nowak et al. (2008b) proposed a heuristic based on a tabu search. Their method provides very reasonable solu-tions as demonstrated by the experiments not only in their paper (Nowak et al., 2008b) but also in ours. However, the computation time seems intensive especially for the class of problems with dynamic transportation requests, including the military cargo-plane routing problem. This paper proposes a more scalable algorithm hybridizing a tabu search for pricing subproblem paused as a single-vehicle routing problem, with a column generation approach based on Dantzig-Wolfe decomposition. As tested on a wide variety of instances, our algorithm produces, in average, a solution of an equiva-lent quality in 10~20% of the computation time of the previous method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.134-141
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• 2022

Transportation in urban area has been getting hard to fulfill the demand on time. There are various uncertainties and obstacles related with road conditions, traffic congestions, and accidents to interrupt the on-time deliveries. With this situation, the last mile logistics has been a keen issue for researchers and practitioners to find the best strategy of the problem. A way to resolve the problem is to use parcel lockers. Parcel locker is a storage that customers can pick up their products. Transportation vehicles deliver the products to parcel lockers instead of all customer sites. Using the parcel lockers, the total delivery costs can be reduced. However, the inconvenience of customer has to increase. Thus, we have to optimal solution to balance between the total delivery costs and customers' inconvenience. This paper formulates a mathematical model to find the optimal solution for the vehicle routing problem and the location problem of parcel lockers. Experimental results provide the viability to find optimal strategy for the routing problem as well as the location problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.168-175
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• 2024

Due to the complexity of urban area, the city vehicle routing problem has been a difficult problem. The problem has involved factors such as parking availability, road conditions, and traffic congestion, all of which increase transportation costs and delivery times. To resolve this problem, one effective solution can be the use of parcel lockers located near customer sites, where products are stored for customers to pick up. When a vehicle delivers products to a designated parcel locker, customers in the vicinity must pick up their products from that locker. Recently, identifying optimal locations for these parcel lockers has become an important research issue. This paper addresses the parcel locker location problem within the context of urban traffic congestion. By considering dynamic environmental factors, we propose a Markov decision process model to tackle the city vehicle routing problem. To ensure more real situations, we have used optimal paths for distances between two nodes. Numerical results demonstrate the viability of our model and solution strategy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2340-2349
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• 2009

In this paper we proposed a hopping routing scheme to resolve the hot spot problem for periodic monitoring services in wireless sensor networks. Our hopping routing scheme constructs load balanced routing path, where an amount of energy consumption of all nodes in the sensor networks is predictable. Load balanced routing paths can be obtained from horizontal hopping transmission scheme which balances the load of the sensor nodes in the same area, and also from vertical hopping transmission scheme which balances the load of the sensor nodes in the other area. The direct transmission count numbers as load balancing parameter for vertical hopping transmission are derived using the energy consumption model of the sensor nodes. The experimental results show that the proposed hopping scheme resolves the hot spot problem effectively. The efficiency of hopping routing scheme is also shown by comparison with other routing scheme such as multi-hop, direct transmission and clustering.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.59-67
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• 2009

This paper proposes a improved bitmap routing protocol, which finds the best energy efficient routing path by minimizing the network overheads and prolongs the overall network lifetime. Jung proposed a bitmap scheme for sensor networks. His scheme uses a bitmap table to represent the connection information between nodes. However, it has a problem that the table size is depends on the number of nodes in the sensor networks. The problem is very serious in the sensor node with a limited memory. Thereby, this paper proposes a improved bitmap routing protocol to solve the problem in Jung's scheme. Proposed protocol over the memory restricted sensor network could optimize the size of bitmap table by applying the deployed network property. Proposed protocol could be used in the diversity of sensor networks due to it has minimum memory overheads.