• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1567-1587
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• 2014

Virtual Machine (VM) resource management is crucial to satisfy the Quality of Service (QoS) demands of various multimedia services in a media cloud platform. To this end, this paper presents a VM resource allocation model that dynamically and optimally utilizes VM resources to satisfy QoS requirements of media-rich cloud services or applications. It additionally maintains high system utilization by avoiding the over-provisioning of VM resources to services or applications. The objective is to 1) minimize the number of physical machines for cost reduction and energy saving; 2) control the processing delay of media services to improve response time; and 3) achieve load balancing or overall utilization of physical resources. The proposed VM allocation is mapped into the multidimensional bin-packing problem, which is NP-complete. To solve this problem, we have designed a Mixed Integer Linear Programming (MILP) model, as well as heuristics for quantitatively optimizing the VM allocation. The simulation results show that our scheme outperforms the existing VM allocation schemes in a media cloud environment, in terms of cost reduction, response time reduction and QoS guarantee.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.353-360
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• 2015

The offshore oil production requires a huge amount of cost and time accompanied by multiple variables due to the peculiar nature of 'offshore'. And every process concerned is controlled by elaborate series of plans for reducing loss of lives, environment and property. This paper treats an optimization problem for offshore oil production and transportation. We present an offshore production and transportation network to define scope of the problem and construct a mixed integer linear programming model to tackle it. To demonstrate the validity of the optimization model presented, some computational experiments based on hypothetical offshore oil fields and demand markets are carried out by using MS Office Excel solver. The downstream of the offshore production and transportation network ends up with the maritime transportation problem distributing the crude oil produced from offshore fields to demand markets. We used MoDiSS(Model-based DSS in Ship Scheduling) which was built to resolve this maritime transportation problem. The paper concludes with the remark that the results of the study might be meaningfully applicable to the real world problems of offshore oil production and transportation.

• Korean Journal of Construction Engineering and Management
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• v.16 no.6
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• pp.53-62
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• 2015

Time-Cost Trade-Off (TCTO) model is an important model in the construction project planning and control area. Two types of Existing TCTO model, continuous and discrete TCTO model, have been developed by researchers. However, Using only one type of model has a limitation to represent a realistic crash scenario of activities in the project. Thus, this paper presents a comprehensive TCTO model that combines a continuous and discrete model. Additional advanced features for non-linear relationship, incentive, and liquidated damage are included in the TCTO model. These features make the proposed model more applicable to the construction project. One CPM network with 6 activities is used to explain the proposed model. The model found an optimal schedule for the example to satisfy all the constraints. The results show that new model can represent more flexible crash scenario in TCTO model.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.336-350
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• 2013

This paper proposes a mathematical modeling-based approach for assessing disaster effects and selecting suitable mitigation alternatives to provide humanitarian relief (HR) supplies, shelter, rescue services, and long-term services after a disaster event. Mitigation steps, such as arrangement of shelter and providing HR items (food, water, medicine, etc.) are the immediate requirements after a disaster. Since governments and non-governmental organizations (NGOs) providing humanitarian aid need to know the requirements of relief supplies and resources for collecting relief supplies, organizing and initiating mitigation steps, a quick assessment of the requirements is the precondition for effective disaster management. Based on satellite images from weather forecasting channels, an area/dimension of the disaster-affected zones and the extent of the overall damage may often be obtained. The proposed approach then estimates the requirements for HR supplies, supporting resources, and rescue services using the census and other government data. It then determines reliable transportation routes, optimum collection and distribution centers, alternatives for resource support, rescue services, and long-term help needed for the disaster-affected zones. A numerical example illustrates the applicability of the model in disaster mitigation planning.

• Journal of the Korea Society for Simulation
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• v.22 no.4
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• pp.149-156
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• 2013

In this research, we dealt with an optimization problem which aims to minimize total cost of resources usage and network routing in a smart node environment. Toward this, we briefly introduced technology trends in smart nodes, methods in resource optimization fields, economic effects of smart network and content delivery (or distribution) network (CDN). Moreover, based on CDN we proposed and implemented a mathematical (mixed integer) programming model to combine replica placement and requests distribution problem (RPRDP) and routing problem. Computational result of an example on RPRDP+Routing problem is also provided.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.945-949
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• 2004

These days there are so many scheduling systems or softwares. But only few scheduling systems have succeeded in the market. In spite of powerful engine and functions, those systems have difficulties to be applied in real processes. In real processes, there are various constraints caused by physical or systematical environments of plants. Those constraints are too many to be handled in the system. This problem makes it difficult for the system to represent the details of processes. In order to resolve this problem, we have developed a specialized scheduling system for a target process. The system could be developed by the experts for target process and researchers for scheduling. In this study, a scheduling system for PVC process has been developed as an MILP (Mixed integer linear programming) model and coded in $Fortran^{TM}$. The scheduling system has been applied to two processes, which have different characteristics. Simulation results indicate that the profit of the target process can be increased by about 5% by implementing the scheduling system.

• IE interfaces
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• v.17 no.spc
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• pp.141-151
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• 2004

As today's business environment has become more and more competitive, forward as well as backward flows of products among members belonging to a supply chain have been increased. The backward flows of products, which are common in most industries, result from increasing amount of products that are returned, recalled, or need to be repaired. Effective management for the backward flows of products has become an important issue for businesses because of opportunities for simultaneously enhancing profitability and customer satisfaction from returned products. Since third party logistics service providers (3PLs) are playing an important role in reverse logistics operations, they should perform two simultaneous logistics operations for a number of different clients who want to improve their logistics operations for both forward and reverse flows. In this case, distribution networks have been independently designed with respect to either forward or backward flows so far. This paper proposes a mixed integer programming model for the design of network integrating both forward and reverse logistics. Since the network design problem belongs to a class of NP-hard problems, we present an efficient heuristic algorithm based on genetic algorithm (GA), of which the performance is compared to the lower bound by Lagrangian relaxation. Finally, the validity of proposed algorithm is tested using numerical examples.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.388-393
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• 2005

Private peering, public peering and transit are three common types of interconnection agreements between providers in the Internet. An important decision that an Internet service provider (ISP) has to make is which private peering/transit ISPs and Internet exchanges (IXs) to connect with to transfer traffic at a minimal cost. In this paper, we deal with the problem to find the minimum cost set of private peering/transit ISPs and IXs for a single ISP. There are given a set of destinations with traffic demands, and a set of potential private peering/transit ISPs and IXs with routing information (routes per destination, the average AS-hop count to each destination, etc.), cost functions and capacities. Our study first considers all the three interconnection types commonly used in real world practices. We show that the problem is NP-hard, and propose a heuristic algorithm for it. We then evaluate the quality of the heuristic solutions for a set of test instances via comparison with the optimal ones obtained by solving a mixed integer programming formulation of the problem. Computational results show that the proposed algorithm provides near-optimal solutions in a fast time.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.10
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• pp.28-37
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• 2011

Though Korea has introduced CBP(Cost Based pool) power trading system since 2001, long-term Generation system planning has been executed by government for Cost minimization every 2 years. Until currently the model which is used for Generation system planning and best-mix only considers cost minimization and total yearly or quarterly electricity demand every year. In a view point of one day power supply operation, technical characteristics, like the ramp up/down rate of total generation system, minimum up/down time and GFRQ(Governor Free Response Quantity), are very important. this paper analyzes Optimal Fuel-Mix for 2022 Korea generation system satisfying these constraints of each fuel type and considering pump storage plants, construction cost and $CO_2$ emission charge Using MILP(Mixed Integer Linear Programming) method. Also the sensitivity analysis which follows in future power industry environmental change accomplished.

• Journal of the Optical Society of Korea
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• v.19 no.1
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• pp.13-21
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• 2015

In recent years energy consumption has become a main concern for network development, due to the exponential increase of network traffic. Potential energy savings can be obtained from a load-adaptive scheme, in which a day can be divided into multiple time periods according to the variation of daily traffic patterns. The energy consumption of the network can be reduced by selectively turning off network components during the time periods with light traffic. However, the time segmentation of daily traffic patterns affects the energy savings when designing multiperiod logical topology in optical wavelength routed networks. In addition, turning network components on or off may increase the overhead of logical topology reconfiguration (LTR). In this paper, we propose two mixed integer linear programming (MILP) models to design the optimal logical topology for multiple periods in IP-over-WDM networks. First, we formulate the time-segmentation problem as an MILP model to optimally determine the boundaries for each period, with the objective to minimize total network energy consumption. Second, another MILP formulation is proposed to minimize both the overall power consumption (PC) and the reconfiguration overhead (RO). The proposed models are evaluated and compared to conventional schemes, in view of PC and RO, through case studies.