• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.201-204
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• 1997

This study is focussed on optimization problems which require allocating the restricted inventory to demand points and assignment of vehicles to routes in order to deliver goods for demand sites with optimal decision. This study investigated an integrated model using three step-by-step approach based on relationship that exists between the inventory allocation and vehicle routing with restricted amount of inventory and transportations. we developed several sub-models such as; first, an inventory-allocation model, second a vehicle-routing model based on clustering and a heuristic algorithms, and last a vehicle routing scheduling model, a TSP-solver, based on genetic algorithm. Also, for each sub-models we have developed computer programs and by a sample run it was known that the proposed model to be a very acceptable model for the inventory-allocation and vehicle routing problems.

• Journal of the Korean Institute of Navigation
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• v.24 no.5
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• pp.385-395
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• 2000

In the transportation literature, many useful decision making models for ship routing and ship scheduling have been studied. But the majority of these studies are on industrial carriers, bulk carriers, or tankers. It is quite recent that a few optimization models have been developed for liner fleet routing and scheduling problems. However there have been few academic studies on decision making models for the routing or scheduling problems of passenger ships in spite of their economic importance in the entire shipping industry. The purpose of this study is to develop analytic decision making models for ship routing and scheduling for the passenger ship fleet. This study gives two optimization models, one is a linear programming model and the other a goal programming model. These two models are solved easy by commercial linear programming softwares and suggest optimal ship routing plans and many other useful implications for passenger ship fleet managers.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.93-99
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• 2011

In this paper, we propose a policy-gradient routing scheme under Reinforcement Learning that can be used adaptive QoS routing. A policy-gradient RL routing can provide fast learning of network environments as using optimal policy adapted average estimate rewards gradient values. This technique shows that fast of learning network environments results in high success rate of routing. For prove it, we simulate and compare with three different schemes.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.70-84
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• 2006

We propose a new distributed QoS routing scheme called pre-computation based selective probing (PCSP). The PCSP scheme is designed to provide an exact solution to the constrained optimization problem with moderate overhead, considering the practical environment where the state information available for the routing decision is not exact. It does not limit the number of probe messages, instead, employs a qualitative (or conditional) selective probing approach. It considers both the cost and QoS metrics of the least-cost and the best-QoS paths to calculate the end-to-end cost of the found feasible paths and find QoS-satisfying least-cost paths. It defines strict probing condition that excludes not only the non-feasible paths but also the non-optimal paths. It additionally pre-computes the QoS variation taking into account the impreciseness of the state information and applies two modified QoS-satisfying conditions to the selection rules. This strict probing condition and carefully designed probing approaches enable to strictly limit the set of neighbor nodes involved in the probing process, thereby reducing the message overhead without sacrificing the optimal properties. However, the PCSP scheme may suffer from high message overhead due to its conservative search process in the worst case. In order to bound such message overhead, we extend the PCSP algorithm by applying additional quantitative heuristics. Computer simulations reveal that the PCSP scheme reduces message overhead and possesses ideal success ratio with guaranteed optimal search. In addition, the quantitative extensions of the PCSP scheme turn out to bound the worst-case message overhead with slight performance degradation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4054-4071
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• 2015

Named-Data Networking (NDN) is one of the promising approaches for the Future Internet to cope with the explosion and current usage pattern of Internet traffic. Content provider mobility in the NDN allows users to receive real-time traffic when the content providers are on the move. However, the current solutions for managing these mobile content providers suffer several issues such as long handover latency, high cost, and non-optimal routing path. In this paper, we survey main approaches for provider mobility in NDN and propose an optimal scheme to support the mobile content providers in the large-scale NDN domain. Our scheme predicts the movement of the provider and uses state information in the NDN forwarding plane to set up an optimal new routing path for mobile providers. By numerical analysis, our approach provides NDN users with better service access delay and lower total handover cost compared with the current solutions.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.5
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• pp.667-674
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• 2011

Data networks at sea will be overlapped networks with not only traditional carriers such as RF, satellites but also BWA like wireless LAN, WiBro, and WCDMA in near future. In this paper, an overlapped MANET model for data networks at sea, and a routing protocol (OMH-MW) selecting optimal transmission medium for each hop in routes are proposed. OMH-MW measures the optimality of each medium regarding the transmission characteristics of each application and those of the medium in together. The most suitable medium to each link is selected as the link in routes. Performances are compared with those of the MWR (Max-Win based Routing protocol searching optimal routes with only one medium).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.475-478
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• 2004

Tool costs can comprise a significant part of the total operating costs of Flexible Manufacturing Systems. We address the problem of determining the optimal processing times of individual operations and routing mix in FMSs with multiple routes for each part type in order to minimize tool cost, subject to meeting a throughput constraint for each part type. The problem is formulated as a nonlinear program superimposed on a closed queueing network of the FMSs under consideration. Numerical examples reveal the potential of our approach for significant saving in tool costs.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1645-1654
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• 2007

In this paper, we study the problem of load balancing routing in clustered-based wireless mesh network in order to enhance the overall network throughput. We first address the problems of cluster allocation in wireless mesh network to achieve load-balancing state. Due to the complexity of the problem, we proposed a simplified algorithm using gradient load-balancing model. This method searches for a localized optimal solution of cluster allocation instead of solving the optimal solution for overall network. To support for load-balancing algorithm and reduce complexity of topology control, we also introduce limited broadcasting between two clusters. This mechanism maintain shortest path between two nodes in adjacent clusters while minimizing the topology broadcasting complexity. The simulation experiments demonstrate that our proposed model achieve performance improvement in terms of network throughput in comparison with other clustering methods.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.4
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• pp.328-337
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• 2004

Tool costs can comprise a significant part of the total operating costs of Flexible Manufacturing Systems. We address the problem of determining the optimal processing times of individual operations and routing mix in FMSs with multiple routes for each part type in order to minimize tool cost, subject to meeting a throughput constraint for each part type. The problem is formulated as a nonlinear program superimposed on a closed queueing network of the FMSs under consideration. Numerical examples reveal the potential of our approach for significant saving in tool costs.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.175-187
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• 2004

We consider the simultaneous selection of part routes for multiple part types in Flexible Manufacturing Systems (FMSs). Using an optimization framework we investigate two alternative route assignment policies. The one, called routing mix policy in the literature, specifies the optimal proportion of each part type to be produced along its alternative routes, assuming that the proportions can be kept during execution. The other one, which we propose and call pallet allocation policy, partitions the pallets assigned to each part type among the routes. The optimization framework used is a nonlinear programming superimposed on a closed queueing network model of an FMS which produces multiple part types with distinct repeated visits to certain workstations. The objective is to maximize the weighted throughput. Our study shows that the simultaneous use of multiple routes leads to reduced bottleneck utilization, improved workload balance, and a significant increase in the FMS's weighted throughput, without any additional capital investments. Based on numerical work, we also conjecture that pallet allocation policy is more robust than routing mix policy, operationally easier to implement, and may yield higher revenues.