• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.93-100
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• 2021

The Ethereum shard system for solving the scalability problem of the blockchain has a load balancing issue, which is modeled as a graph partitioning problem. In this paper, we propose an adaptive online weighted graph partitioning algorithm that can negotiate between two utility of the shard system using the game theory's bargaining solution. The bargaining solution is an axiomatic solution that can fairly determine the points of conflict of utility. The proposed algorithm was improved to apply the existing online graph partitioning algorithm to the weighted graph, and load balancing was performed efficiently through the design considering the situation of the sharding system using the extension of Nash bargaining solution, which is extended to apply solution to non-convex feasible set of bargaining problem. As a result of the experiment, it showed up to 37% better performance than typical load balancing algorithm of shard system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.57-78
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• 2005

The vehicle routing problem (VRP) is to determine a set of feasible vehicle routes, one for each vehicle, such that each customer is visited exactly once and the total distance travelled by the vehicles is minimized. A feasible route is defined as a simple circuit including the depot such that the total demand of the customers in the route does not exceed the vehicle capacity. While there have been significant advances recently in exact solution methodology, the VRP is not a well solved problem. We find most approaches still relying on the branch and bound method. These approaches employ various methodologies to compute a lower bound on the optimal value. We introduce a new modelling approach, termed route-splitting, for the VRP that allows us to address problems whose size is beyond the current computational range of set-partitioning models. The route-splitting model splits each vehicle route into segments, and results in more tractable subproblems. Lifting much of the burden of solving combinatorially hard subproblems, the route-splitting approach puts more weight on the LP master problem, Recent breakthroughs in solving LP problems (Nemhauser, 1994) bode well for our approach. Lower bounds are computed on five symmetric VRPs with up to 199 customers, and eight asymmetric VRPs with up to 70 customers. while it is said that the exact methods developed for asymmetric instances have in general a poor performance when applied to symmetric ones (Toth and Vigo, 2002), the route splitting approach shows a competent performance of 93.5% on average in the symmetric VRPs. For the asymmetric ones, the approach comes up with lower bounds of 97.6% on average. The route-splitting model can deal with asymmetric cost matrices and non-identical vehicles. Given the ability of the route-splitting model to address a wider range of applications and its good performance on asymmetric instances, we find the model promising and valuable for further research.

• Journal of the Korean Home Economics Association
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• v.38 no.9
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• pp.33-40
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• 2000

The purpose of this proper is to set up the sizing system of the lower, which would be a guide for obese women for selecting ready-to-wear of suitable size. This study was carried out on 130 obese women and was done by cluster analysis with two(waist girth and hip girth) or three(abdomen circumference, hip girth and crotch length) variables. The results were as fellows: First, it was found that 3-5 sizes were suitable by cluster analysis with two variable. Second, 3-4 sizes were suitable with three variables. Finally, the number of sizes to product was 5 with two variables as a feasible solution, and 4 with three variables.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.941-947
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• 2011

This paper deals with the consensus problem for multi-agent linear dynamic systems with directed communication topology. All the agents are identical high-order linear systems and their state information is exchanged through a communication network with directed graph. It is shown that a consensus is achieved if there exists a feasible solution to a set of linear matrix inequalities obtained for a simultaneous stabilization problem for multiple systems. Examples are presented to show the effectiveness of the proposed method.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.3
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• pp.1-15
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• 2000

In this paper, we propose a practical cut generation method based on the Chvatal-Gomory procedure for the (0, 1)-Knapsack problem with a variable capacity. For a given set N of n items each of which has a positive integral weight and a facility of positive integral capacity, a feasible solution of the problem is defined as a subset S of N along with the number of facilities that can satisfy the sum of weights of all the items in S. We first derive a class of valid inequalities for the problem using Chvatal-Gomory procedure, then analyze the associated separation problem. Based on the results, we develop an affective cut generation method. We then analyze the theoretical strength of the inequalities which can be generated by the proposed cut generation method. Preliminary computational results are also presented which show the effectiveness of the proposed cut generation method.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.67-69
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• 2009

This paper deals with the consensus problem for multi-agent linear dynamic systems with parameter uncertainties. All the agents are identical high-order linear systems with parameter uncertainties and their state information is exchanged through a communication network. It is shown that a consensus is achieved if there exists a feasible solution to a set of linear matrix inequalities obtained for a simultaneous stabilization problem for multiple systems. A numerical example is presented to show the effectiveness of the proposed method.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.88-90
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• 2009

This paper deals with the consensus problem for multi-agent linear dynamic systems with communication delay. All the agents are identical high-order linear systems and their state information is exchanged through a communication network with constant communication delay. It is shown that a consensus is achieved if there exists a feasible solution to a set of linear matrix inequalities obtained for a simultaneous stabilization problem for multiple systems with delay. A numerical example is presented to show the effectiveness of the proposed method.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.355-361
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• 2010

This paper addresses a mathematical approach to decision making in a real-world material distribution situation. The problem is characterized by a low-volume and highly-varied mix of products, therefore there is a lot of material movement between the facilities. This study focuses especially on the transportation scheduler with a tool that can be used to quantitatively analyze the volume of material moved, the type of truck to be used, production schedules, and due dates. In this research, we have developed a mixed integer programming problem using the minimum cost, multiperiod, multi-commodity network flow approach that minimizes the overall material movement costs. The results suggest that the optimization approach provides a set of feasible solution routes with the objective of reducing the overall fleet cost.

• Kyungpook Mathematical Journal
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• v.64 no.1
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• pp.69-94
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• 2024

In this paper, we introduce an inertial self-adaptive projection method using Bregman distance techniques for solving pseudomonotone equilibrium problems in reflexive Banach spaces. The algorithm requires only one projection onto the feasible set without any Lipschitz-like condition on the bifunction. Using this method, a strong convergence theorem is proved under some mild conditions. Furthermore, we include numerical experiments to illustrate the behaviour of the new algorithm with respect to the Bregman function and other algorithms in the literature.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5103-5115
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• 2015

In radar imaging, a target is usually consisted of a few strong scatterers which are sparsely distributed. In this paper, an improved sparse signal recovery algorithm based on smoothed l₀ (SL0) norm method is proposed to achieve high resolution ISAR imaging with limited pulse numbers. Firstly, one new smoothed function is proposed to approximate the l₀ norm to measure the sparsity. Then a single loop step is used instead of two loop layers in SL0 method which increases the searching density of variable parameter to ensure the recovery accuracy without increasing computation amount, the cost function is undated in every loop for the next loop until the termination is satisfied. Finally, the new set of solution is projected into the feasible set. Simulation results show that the proposed algorithm is superior to the several popular methods both in terms of the reconstruction performance and computation time. Real data ISAR imaging obtained by the proposed algorithm is competitive to several other methods.