• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.402-408
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• 2002

Multicast technology allows the transmission of data from one source node to a selected group of destination nodes. Multicast routes typically use trees, called multicast routing trees, to minimize resource usage such as cost and bandwidth by sharing links. Moreover, the quality of service (QoS) is satisfied by distributing data along a path haying no more than a given number of arcs between the root node of a session and a terminal node of it in the routing tree. Thus, a multicast routing tree for a session can be represented as a hop constrained Steiner tree. In this paper, we consider the hop-constrained multicast route packing problem with bandwidth reservation. Given a set of multicast sessions, each of which has a hop limit constraint and a required bandwidth, the problem is to determine a set of multicast routing trees in an arc-capacitated network to minimize cost. We propose an integer programming formulation of the problem and an algorithm to solve it. An efficient column generation technique to solve the linear programming relaxation is proposed, and a modified cover inequality is used to strengthen the integer programming formulation.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1213-1216
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• 2005

In this paper, we suggested the integer linear programming (ILP) models that went through constraint scheduling to simple cycle operation during the delay time. The delayed scheduling can determine a schedule with a near-optimal number of control steps for given fixed hardware constraints. In this paper, the resource-constrained problem is addressed, for the DFG optimization for multiprocessor design problem, formulating ILP solution available to provide optimal solution. The results show that the scheduling method is able to find good quality schedules in reasonable time.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.3
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• pp.11-22
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• 1997

The aim of this paper is to develop the B & B type algorithms for globally minimizing concave function under 0-1 knapsack constraint. The linear convex envelope underestimating the concave object function is introduced for the bounding operations which locate the vertices of the solution set. And the simplex containing the solution set is sequentially partitioned into the subsimplices over which the convex envelopes are calculated in the candidate problems. The adoption of cutting plane method enhances the efficiency of the algorithm. These mean valid inequalities with respect to the integer solution which eliminate the nonintegral points before the bounding operation. The implementations are effectively concretized in connection with the branching stategys.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.118-126
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• 2009

This research investigates the problem of minimizing setup costs in resequencing jobs having first-in, first-out(FIFO) constraints at conveyorized production or assembly systems. Sequence changing at conveyor junctions in these systems is limited due to FIFO restriction. We first define the general problem of resequencing jobs to workstations satisfying precedence relationships between jobs(Generalized Sequential Ordering Problem, GSOP). Then we limit our scope to FIFO precedence relationships which is the conveyor selection problem at a diverging junction(Diverging Sequential Ordering Problem, DSOP), modeling it as a 0-1 integer program. With the capacity constraint removed, we show that the problem can be modeled as an assignment problem. In addition, we proposed and evaluated the heuristic algorithm for the case where the capacity constraint cannot be removed. Finally, we discuss the case study which motivated this research and numerical results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2003-2021
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• 2020

Today's computer systems are widely integrated with CPU and GPU to achieve considerable performance, but energy consumption of such system directly affects operational cost, maintainability and environmental problem, which has been aroused wide concern by researchers, computer architects, and developers. To cope with energy problem, we propose a task-scheduling framework to reduce energy under performance constraint by rationally allocating the tasks across the CPU and GPU. The framework first collects the estimated energy consumption of programs and performance information. Next, we use above information to formalize the scheduling problem as the 0-1 knapsack problem. Then, we elaborate our experiment on typical platform to verify proposed scheduling framework. The experimental results show that our proposed algorithm saves 14.97% energy compared with that of the time-oriented policy and yields 37.23% performance improvement than that of energy-oriented scheme on average.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.4
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• pp.40-45
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• 2002

An AS/RS construction cost minimization model under throughput rate requirement constraint has been developed, whose objective function includes S/R machine cost, storage rack cost, and interrace conveyor cost. S/R machine cost is a function of the storage rack height, the unit load weight, and the control logic used by the system, while storage rack cost is a function of the storage rack height, the weight and the volume of the unit load. Since the model is a nonlinear integer programming problem which is very hard to solve exactly with large problem size, a solution procedure is developed to determine the height and the length of the storage rack with a fixed number of S/R machines, while increasing the number of S/R machines one by one to meet the throughput rate requirement.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.410-417
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• 2002

We consider the constraint based explicit routing problem in MPLS based IP Network. In this problem, we are given a set of traffic demands and a network with different link capacities. The problem is to assign the demand commodities to the paths in the network while minimizing the maximum link load ratio. We formulate this problem as an integer programming problem and propose an efficient column generation technique. To strengthen the formulation, we consider some valid inequalities. We also incorporate the column generation technique with variable fixing scheme Computational results show that the algorithm gives high quality solutions in a short execution time.

• Journal of the Korea Society for Simulation
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• v.9 no.4
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• pp.41-50
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• 2000

We have many simulation constraints to meet as a modeled system becomes large and complex. Real-time simulations are the examples in that they are constrained by certain non-function constraints (e.g., timing constraints). In this paper, an enhanced hierarchical modeling methodology is proposed to efficiently deal with constraint-simulations. The proposed modeling method enhances hierarchical modeling methods to provide multi-resolution model. A simulation model is composed by determining the optimal level of abstraction that is guaranteed to meet the given simulation constraints. Four modeling activities are defined in the proposed method: 1) Perform the logical architectural design activity to produce a multi-resolution model, 2) Organize abstraction information of the multi-resolution model with AT (Abstraction Tree) structure, 3) Formulate the given constraints based on U (Integer Programming) approach and embrace the constraints to AT, and 4) Compose a model based on the determined level of abstraction with which the multi-resolution model can satisfy all given simulation constraints. By systematically handling simulation constraints while minimizing the modeler's interventions, we provide an efficient modeling environment for constraint-simulations.

• Journal of Navigation and Port Research
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• v.30 no.7
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• pp.561-566
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• 2006

In this paper, we propose a new ship scheduling set packing model considering limited risk or variance. The set packing model is used in many applications, such as vehicle routing, crew scheduling, ship scheduling, cutting stock and so on. As long as the ship scheduling is concerned, there exits many unknown external factors such as machine breakdown, climate change and transportation cost fluctuation. However, existing ship scheduling models have not considered those factors apparently. We use a quadratic set packing model to limit the variance of expected cost of ship scheduling problems under stochastic spot rates. Set problems are NP-complete, and additional quadratic constraint makes the problems much harder. We implement Kelley's cutting plane method to replace the hard quadratic constraint by many linear constrains and use branch-and-bound algorithm to get the optimal integral solution. Some meaningful computational results and comments are provided.

• Communications of the Korean Mathematical Society
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• v.32 no.1
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• pp.225-231
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• 2017

Baskoro et al. [1] provided some constructions of new super edge-magic graphs from some old ones by attaching 1, 2, or 3 pendant vertices and edges. In this paper, we introduce (q, m)-super edge-magic total labeling and we give a construction of new super edge-magic graphs by attaching n pendant vertices and edges under some conditions, for any positive integer n. Also, we give a constraint on our construction.