• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.53-58
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• 2023

As smartphones increasingly support the execution of various applications, the function of virtual memory swapping is becoming important. However, unlike traditional computer systems, mobile platforms do not basically support swapping. This is because swapping results in frequent writes to flash memory, which may degrade the performance of smartphone's storage significantly. To cope with this situation, this paper suggests two multi-swap architectures, hierarchical swapping and hybrid swapping, and compares their performance quantitatively. Specifically, this paper shows that hybrid swapping with the consideration of single-access data can reduce swapping traffic to flash memory, and improve the performance compared to traditional swapping.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.80-89
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• 2013

This paper presents an efficient approach for solving economic dispatch (ED) problems with nonconvex cost functions using a 'Mean-Variance Optimization (MVO)' algorithm with Kuhn-Tucker condition and swap process. The aim of the ED problem, one of the most important activities in power system operation and planning, is to determine the optimal combination of power outputs of all generating units so as to meet the required load demand at minimum operating cost while satisfying system equality and inequality constraints. This paper applies Kuhn-Tucker condition and swap process to a MVO algorithm to improve a global minimum searching capability. The proposed MVO is applied to three different nonconvex ED problems with valve-point effects, prohibited operating zones, transmission network losses, and multi-fuels with valve-point effects. Additionally, it is applied to the large-scale power system of Korea. The results are compared with those of the state-of-the-art methods as well.

• Journal of the Korea Society of Computer and Information
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• v.20 no.7
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• pp.33-40
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• 2015

The time slot assignment problem (TSAP) or Satellite Communications scheduling problem (SCSP) for a satellite performs $n{\times}n$ ground station data traffic switching has been known NP-hard problem. This paper suggests $O(n^2)$ time complexity algorithm for TSAP of a satellite that performs $n^2{\times}n^2$ ground station data traffic switching. This problem is more difficult than $n{\times}n$ TSAP as NP-hard problem. Firstly, we compute the average traffic for n-transponder's basic coverage zone and applies ground station exchange method that swap the ground stations until all of the transponders have a average value as possible. Nextly, we transform the D matrix to $D_{LB}$ traffic matrix that sum of rows and columns all of transponders have LB. Finally, we select the maximum traffic of row and column in $D_{LB}$, then decide the duration of kth switch mode to minimum traffic from selected values. The proposed algorithm can be get the optimal solution for experimental data.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.187-190
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• 2003

Many manufacturing companies consider the integrated and concurrent scheduling because they need the global optimization technology that could manufacture various products more responsive to customer needs. In this paper, we propose an advanced scheduling model to generate the schedules considering resource constraints and precedence constraints in make-to-order (MTO) manufacturing environments. Precedence of work- in-process(WIP) and resources constraints have recently emerged as one of the main constraints in advanced scheduling problems. The advanced scheduling problems is formulated as a multiobjective mathematical model for generating operation schedules which are obeyed resources constraints, alternative workstations of operations and the precedence constraints of WIP in MTO manufacturing. For effectively solving the advanced scheduling problem, the multi-objective hybrid genetic algorithm (m-hGA) is proposed in this paper. The m-hGA is to minimize the makespan, total flow time of order, and maximum tardiness for each order, simultaneously. The m-hGA approach with local search-based mutation through swap mutation is developed to solve the advanced scheduling problem. Numerical example is tested and presented for advanced scheduling problems with various orders to describe the performance of the proposed m-hGA.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.5-14
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• 2018

This study is motivated based on concern from some renowned scholars and central bankers whom have raised the issue of the sustainability of the International Monetary System (IMS). Using the panel data set of four major international currencies, USD, JPY, EUR and GBP from 1973 to 2013 with Pooled Mean Group (PMG) estimator, to re-examine whether Triffin dilemma still exists through investigating the relationship between the reserve share, current account balance and real effective exchange rate. The evidence from the result indicates that Triffin dilemma exists only in the long run, and shows that in the long-run, current account balance is proportionate to the increased real effective exchange rate while varies inversely with the reserve shares. However, the estimation for the short-run is not significant to prove the existence of Triffin dilemma. In addition, we investigated the non-dollar panel sample and found that the international monetary system still suffers from Triffin dilemma even without the dollar. To overcome Triffin dilemma, immediate step such as having currency swap mechanism is recommended. In medium term, a multi-polar Monetary System is suggested, and in the longer time, a supranational currency will be used to replace all the currencies in the world.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.171-181
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• 2008

Home care, known also as domiciliary care, is part of the community care service that is a responsibility of the local government authorities in the UK as well as many other countries around the world. The aim is to provide the care and support needed to assist people, particularly older people, people with physical or learning disabilities and people who need assistance due to illness to live as independently as possible in their own homes. It is performed primarily by care workers visiting clients' homes where they provide help with daily activities. This paper is concerned with the dispatching of care workers to clients in an efficient manner. The optimized routine for each care worker determines a schedule to achieve the minimum total cost (in terms of distance traveled) without violating the capacity and time window constraints. A collaborative population-based meta-heuristic called Particle Swarm Optimization (PSO) is applied to solve the problem. A particle is defined as a multi-dimensional point in space which represents the corresponding schedule for care workers and their clients. Each dimension of a particle represents a care activity and the corresponding, allocated care worker. The continuous position value of each dimension determines the care worker to be assigned and also the assignment priority. A heuristic assignment scheme is specially designed to transform the continuous position value to the discrete job schedule. This job schedule represents the potential feasible solution to the problem. The Earliest Start Time Priority with Minimum Distance Assignment (ESTPMDA) technique is developed for generating an initial solution which guides the search direction of the particle. Local improvement procedures (LIP), insertion and swap, are embedded in the PSO algorithm in order to further improve the quality of the solution. The proposed methodology is implemented, tested, and compared with existing solutions for some 'real' problem instances.