• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.12
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• pp.597-602
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• 2005

The introduction of competition in electricity market emphasizes the importance of sufficient transmission capacities to guarantee various electricity transactions. Therefore, when dispatch scheduling, transmission security constraints should be considered for the economic and stable electric power system operation. In this paper, we propose an optimal dispatch scheduling algorithm incorporating transmission security constraints. For solving these constraints, the dispatch scheduling problem is decomposed into a master problem to calculate a general optimal power flow (OPF) without transmission security constraints and several subproblems to inspect the feasibility of OPF solution under various transmission line contingencies. If a dispatch schedule given by the master problem violates transmission security constraints, then an additional constraint is imposed to the master problem. Through these iteration processes between the master problem and subproblems, an optimal dispatch schedule reflecting the post-contingency rescheduling is derived. Moreover, since interruptible loads can positively participate as generators in the competitive electricity market, we consider these interruptible loads active control variables. Numerical example demonstrates efficiency of the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.9-16
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• 2017

The course timetabling problem is a problem assigning a set of subjects to the given classrooms and different timeslots, while satisfying various hard constraints and soft constraints. This problem is defined as a constraint satisfaction optimization problem and is known as an NP-complete problem. Various methods has been proposed such as integer programming, constraint programming and local search methods to solve a variety of course timetabling problems. In this paper, we propose an iterative improvement search method to solve the problem based on constraint programming. First, an initial solution satisfying all the hard constraints is obtained by constraint programming, and then the solution is repeatedly improved using constraint programming again by adding new constraints to improve the quality of the soft constraints. Through experimental results, we confirmed that the proposed method can find far better solutions in a shorter time than the manual method.

• 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.

• Journal of the Korea Safety Management & Science
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• v.7 no.1
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• pp.159-166
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• 2005

It is not difficult to see the road repairing. There are many and various machines which crush road surface. The efficiency and power of the machine depend on crushing head-shape, crushing interval, crushing load, crushing stress, machine's dropping height and roller's kind. The objective of this study is to select the optimal model among ten models of crushing machine with constraints such as crushing depth, variation, and crushed particle size. And then this paper provides the valid theoretical base on selected model. The data for this study are chosen from the site of construction in Kangnung during three months (2004. 6. 1${\~}$2004. 8. 31). The provided methodology in this paper will be fruitful not only for the selection of crushing machine but also for the aspects of construction period, cost, work efficacy according to the condition from the various sites of construction.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.2
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• pp.94-103
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• 1994

In testing for practical scan disigned logic circuits, there may exist logic value constraints on some part of primary inputs due to various requirements on design and test. This paper presents a logic value system called taboo logic values which targets the test pattern generation of logic circuits under logic value constraints. The taboo logic system represents the logic value constraints and identifies additional logic value constraints through the implication of the tqaboo logic values using a taboo logic calculus. Those identified logic value constraints will guide the search during the test pattern generation of avoid the unfruitful searches and to identify redundant faults due to the logic value constraints very quickly. Finally, experimental results on ISCAS85 benchmark circuits will demonstrate the efficiency of the taboo logic values.

• Journal of the Society of Naval Architects of Korea
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• v.28 no.2
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• pp.187-194
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• 1991

Vibration analysis methods of a beam-column with elastically restrained ends and various intermediate constraints such as rectilinear springs, rotational springs and concentrated masses are presented. Firstly, an exact method of solutions based on Hamilton's principle and Laplace transform method is shown. This method of solutions is very complicate in cases of having Intermediate constraints more than two. Therefore, Rayleigh-Ritz method using the eigenfunctions of the base system, the system without intermediate constraints, are also investigated. Extensive numerical examples carried out for comparisons with known published works show that the latter method has easy adaptability for wide varieties of boundary conditions and intermediate constraints, and gloves good accuracy for various intermediate constraints with reasonable number of terms in construction of a trial function.

• Journal of Information Technology Applications and Management
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• v.9 no.1
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• pp.27-44
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• 2002

Performance evaluations of database algorithms are usually conducted on a set of queries for a given test database. For more detailed evaluation results, it is often necessary to use different query workloads several times. Each query workload should reflect the querying patterns of the application domain in real world, which are non-uniform in the usage frequencies of attributes in queries of the workload for a given database. It is not trivial to generate many different query workloads manually, while considering non-uniform distributions of attributes'usage frequencies. In this paper we propose a technique to generate non-uniform distributions, which will help construct query workloads more efficiently. The proposed algorithm generates a query-attribute usage distribution based on given constraints on usage frequencies of attributes and qreries. The algorithm first allocates as many attributes to queries as Possible. Then it corrects the distribution by considering attributes and queries which are not within the given frequency constraints. We have implemented and tested the performance of the proposed algorithm, and found that the algorithm works well for various input constraints. The result of this work could be extended to help automatically generate SQL queries for various database performance benchmarking.

• The Journal of Korea Robotics Society
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• v.10 no.3
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• pp.133-138
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• 2015

This paper presents a modified task structure of coupled-constraints consensus based bundle algorithm especially to resolve the cooperative transportation problem. The cooperative transportation mission has various types of constraints. A modified framework to generate activities and subtasks to solve time and task constraints of the transportation mission by using coupled-constraints consensus based bundle algorithm is suggested. In this paper modifications on task structure, reward function and arrival time calculation are suggested to handle the constraints of cooperative transportation mission.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.11a
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• pp.40-44
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• 2004

A fact that limits a company's ability to achieve more of its goal is referred to as a 'constraint' shipbuilding industries need to identify and manage constraints. The theory of constraints is evolved out of the problems of bottleneck formation. This happens and is conserved for the formulation if various real time problems for arriving standard uniquely addressed problems If, for example, the goal of a shipbuilding industry is to make money now and in the future, it is suggested that TOC will enable th mangers of the company to do so. TOC, focuses the organization scare resources on improving the performance of the true constraints, and therefore the bottom line of the organization. An attempt is made for the implantation of the theory into real world shipyard decision support mechanism.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.32-37
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• 2015

In the fields of plant layout optimization, the main goal is to minimize the construction cost including pipelines as satisfying all constraints such as safety and operating issues. However, what is the lacking of considerations in previous researches is to consider proper safety and maintenance spaces for a complex plant. Based on the mathematical programming, MILP(Mixed Integer Linear Programming) problems including various constraints can be formulated to find the optimal solution which is to achieve the best economic benefits. The objective function of this problem is the sum of piping cost, pumping cost and area cost. In general, many conventional optimization solvers are used to find a MILP problem. However, it is really hard to solve this problem due to complex inequality and equality constraints, since it is impossible to use the derivatives of objective functions and constraints. To resolve this problem, the PSO (Particle Swarm Optimization), which is one of the representative sampling approaches and does not need to use derivatives of equations, is employed to find the optimal solution considering various complex constraints in this study. The EO (Ethylene Oxide) plant is tested to verify the efficacy of the proposed method.