• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3876-3895
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• 2014

Recently, Heterogeneous Network (HetNet) with Coordinated Multi-Point (CoMP) scheme is introduced into Long Term Evolution-Advanced (LTE-A) systems to improve digital services for User Equipments (UEs), especially for cell-edge UEs. However, Radio Resource Management (RRM), including Resource Block (RB) scheduling and Power Allocation (PA), in this scenario becomes challenging, due to the intercell cooperation. In this paper, we investigate the RRM problem for downlink transmission of HetNet system with Joint Processing (JP) CoMP (both joint transmission and dynamic cell selection schemes), aiming at maximizing weighted sum data rate under the constraints of both transmission power and backhaul capacity. First, joint RB scheduling and PA problem is formulated as a constrained Mixed Integer Programming (MIP) which is NP-hard. To simplify the formulation problem, we decompose it into two problems of RB scheduling and PA. For RB scheduling, we propose an algorithm with less computational complexity to achieve a suboptimal solution. Then, according to the obtained scheduling results, we present an iterative Karush-Kuhn-Tucker (KKT) method to solve the PA problem. Extensive simulations are conducted to verify the effectiveness and efficiency of the proposed algorithms. Two kinds of JP CoMP schemes are compared with a non-CoMP greedy scheme (max capacity scheme). Simulation results prove that the CoMP schemes with the proposed RRM algorithms dramatically enhance data rate of cell-edge UEs, thereby improving UEs' fairness of data rate. Also, it is shown that the proposed PA algorithms can decrease power consumption of transmission antennas without loss of transmission performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.143-150
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• 2019

We focus on the weapon target assignment and fire scheduling problem (WTAFSP) with the objective of minimizing the makespan, i.e., the latest completion time of a given set of firing operations. In this study, we assume that there are m available weapons to fire at n targets (> m). The artillery attack operation consists of two steps of sequential procedure : assignment of weapons to the targets; and scheduling firing operations against the targets that are assigned to each weapon. This problem is a combination of weapon target assignment problem (WTAP) and fire scheduling problem (FSP). To solve this problem, we define the problem with a mixed integer programming model. Then, we develop exact algorithms based on a dynamic programming technique. Also, we suggest how to find lower bounds and upper bounds to a given problem. To evaluate the performance of developed exact algorithms, computational experiments are performed on randomly generated problems. From the results, we can see suggested exact algorithm solves problems of a medium size within a reasonable amount of computation time. Also, the results show that the computation time required for suggested exact algorithm can be seen to increase rapidly as the problem size grows. We report the result with analysis and give directions for future research for this study. This study is meaningful in that it suggests an exact algorithm for a more realistic problem than existing researches. Also, this study can provide a basis for developing algorithms that can solve larger size problems.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.6
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• pp.642-647
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• 2014

In this paper, a hybrid genetic algorithm (HGA) approach is proposed for an n-job, m-machine flow shop scheduling problem with limited capacity buffers with blocking in which the objective is to minimize the total stretch. The stretch of a job is the ratio of the amount of time the job spent before its completion to its processing time. HGA adopts the idea of seed selection and development in order to improve the exploitation and exploration power of genetic algorithms (GAs). Extensive computational experiments have been conducted to compare the performance of HGA with that of GA.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.163-171
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• 2006

This paper considers a scheduling problem to minimize the sum of the associated scheduling (production/delivery times) cost and the delivery cost for an integrated system of a single production machine and various transportation vehicles with transportation mode selection allowed. Each transportation mode is provided with a fixed number of vehicles at the associated delivery time and cost. The proposed problem is characterized as being NP-hard. Some solution properties are also characterized. Therewith, three heuristic algorithms (called SPT-based, LWF-based and WSPT-based heuristic) and a branch-and-bound algorithm are derived. In order to evaluate the effectiveness and efficiency of the proposed algorithms, computational experiments are made with some numerical instances.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.15-27
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• 1998

In the parallel processing systems, a compiler partitions a loaded program into tasks, allocates the tasks on multiple processors and schedules the tasks on each allocated processor. In this paper we suggest a Genetic Algorithm(GA) based scheduling method to find an optimal allocation and sequence of tasks on each Processor. The suggested method uses a chromosome which consists of task sequence and binary string that represent the number and order of tasks on each processor respectively. Two correction algorithms are used to maintain precedency constraints of the tasks in the chromosome. This scheduling method determines the optimal number of processors within limited numbers, and then finds the optimal schedule for each processor. A result from computational experiment of the suggested method is given.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.87-101
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• 2008

This paper considers an order scheduling model to minimize the total weighted tardiness of orders. Each order requires different types of products. Each type of product is manufactured on its dedicated machine specified in advance. The completion time of each order is represented by the time when all the products belonging to the order are completed. The objective of this paper is to find the optimal production schedule minimizing the total weighted tardiness of a finite number of orders. In the problem analysis, we first derive a powerful solution property to determine the sequence of two consecutive orders. Moreover, two lower bounds of objective are derived and tested along with the derived property within a branch-and-bound scheme. Two efficient heuristic algorithms are also developed. The overall performances of the proposed property, branch-and-bound and heuristic algorithms are evaluated through various numerical experiments.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.119-124
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• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.884-887
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• 2002

This paper considers a scheduling problem of routers with VOQ(Virtual Output Queue)s, where the router has an N ${\times}$N port input-queued switch and each input queue is composed of N VOQs. The objective of the paper is to develope scheduling algorithms which minimize mean tardiness under a common due date. The paper characterizes the optimal solution properties. Based upon the characterization, a integer programming is formulated for the optimal solution and two optimal solution algorithms are developed for two special cases of 2 ${\times}$2 switch and N${\times}$N switch with identical traffic.

• Korean Management Science Review
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• v.33 no.2
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• pp.1-10
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• 2016

We treats a job scheduling in a 2-machine flow-shop problem with outsourcing strategy allowed. Jobs in the first machine are processed in-house or outsourced to the other companies. In this paper, all the considered jobs are determined to be in-house processed or outsourced. When a job is outsourced, then the firm should pay an outsourcing cost additionally. We want to minimize the sum of the outsourcing costs and the total completion times of finished jobs. In this paper, some solution properties are characterized, and then some heuristic algorithms and a branch-and-bound solution algorithm are derived. This paper evaluates finally the performance of the proposed algorithms during the numerical tests.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.4
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• pp.63-71
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• 2003

This paper analyses a deterministic scheduling problem concerned with manufacturing multiple types of components at a pre-assembly stage composed of parallel fabrication machines. Each component part is machined on a fabrication machine specified in advance. The manufactured components are subsequently assembled into products. The completion time of a job(product) is measured by the latest completion time of its all components at the pre-assembly stage. The problem has the objective measure of minimizing the total weighted completion time of a finite number of jobs. Two lower bounds are derived and tested in a branch-and-bound scheme. Also, three constructive heuristic algorithms are developed based on the machine aggregation and greedy strategies. Some empirical evaluation of the performance of the proposed branch-and-bound and heuristic algorithms are also performed.