• Journal of Power System Engineering
• /
• v.2 no.3
• /
• pp.60-67
• /
• 1998

Edge detection is the first step and very important step in image analysis. We cast edge detection as a problem in cost minimization. This is achieved by the formulation of a cost function that evaluates the quality of edge configurations. The cost function can be used as a basis for comparing the performances of different detectors. This cost function is made of desirable characteristics of edges such as thickness, continuity, length, region dissimilarity. And we use a simulated annealing algorithm for minimum of cost function. Simulated annealing are a class of adaptive search techniques that have been intensively studied in recent years. We present five strategies for generating candidate states. Experimental results(building image and test image) which verify the usefulness of our simulated annealing approach to edge detection are better than other operator.

• Journal of Korean Institute of Industrial Engineers
• /
• v.24 no.2
• /
• pp.175-183
• /
• 1998

When a product is designed, tolerances must be given to the product so that required functions are guaranteed and production costs are minimized. In this research, a model is suggested which allocates tolerances to components optimally according to the STA(Statistical Tolerance Allocation) method. Taking into account the concept that dimensional errors have characteristics of statistical distributions, this model presents the discrete pseudo-boolean approach for the tolerance optimization by minimizing the tolerance cost and the quality loss cost. In this approach, two methods are proposed for the reduction of the problem scale; 1) a method for converting the minimization model for casts into the maximization model for cost savings, and 2) procedures to reduce the number of constraints and variables.

• The Transactions of the Korea Information Processing Society
• /
• v.3 no.2
• /
• pp.348-358
• /
• 1996

If a method of character region extraction will have general purposes, it could not but make use of common features which all target images have. This paper suggests these common features should be considered as the coalitions for the region to be extracted within a framework of the cost minimization. The method suggested above could be effective by minimizing a cost function estmating the extent that character regions satify quantitatively the features, through Simulated Annealing Method. This method has an uniqueness in that it defines the cost function. Experimental result verify the usefulness of this cost minimization approach to characer region extraction.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2001.10a
• /
• pp.201-210
• /
• 2001

In this study, large-scale distributed design approach for a life cycle cost (LCC) optimization of steel box girder bridges was implemented. A collaborative optimization approach is one of the multidisciplinary design optimization approaches and it has been proven to be best suited for distributed design environment. The problem of optimum LCC design of steel box girder bridges is formulated as that of minimization of the expected total LCC that consists of initial cost maintenance cost expected retrofit costs for strength, deflection and crack. To discuss the possibility of the application for the collaborative optimization of steel box girder bridges, the results of this algorithm are compared with those of single level algorithm. From the numerical investigations, the collaborative optimization approach proposed in this study may be expected to be new concepts and design methodologies associated with the LCC approach.

• Journal of Korean Society for Quality Management
• /
• v.23 no.4
• /
• pp.148-156
• /
• 1995

The past approach to burn-in optimization have been focused mainly in cost minimization problem during entire product life cycle. But in the case of practical application, burn-in optimization under reliability restriction might be preferred to burn-in optimization by cost minimization. Accordingly this paper shows real examples which estimate the practical burn-in period through application of heuristic method and select the best reliability model through comparison of reliability performance measures.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.12
• /
• pp.3096-3117
• /
• 2013

To execute the performance driven Grid applications, an effective and scalable workflow scheduling is seen as an essential. To optimize cost & makespan, in this paper, we propose a Scalable Cost-Time Trade-off (SCTT) model for scheduling workflow tasks. We have developed a heuristic algorithm known as Scalable Cost-Time Trade-off Scheduling (SCTTS) with a lower runtime complexity based on the proposed SCTT model. We have compared the performance of our proposed approach with other heuristic and meta-heuristic based scheduling strategies using simulations. The results show that the proposed approach improves performance and scalability with different workflow sizes, task parallelism and heterogeneous resources. This method, therefore, outperforms other methods.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1998.10a
• /
• pp.151-158
• /
• 1998

This paper presents an optimal decision model for minimizing the life-cycle cost of steel box girder bridges. The point is that it takes into account service life process as a whole, and the life-cycle costs include initial (design, testing, and construction) costs, maintenance costs and expected failure costs. The problem is formulated as that of minimization of expected total life-cycle cost with respect to the design variables. The optimal solution identifies those values of the decision variables that result in minimum expected total cost. The performance constraints in the form of flexural failure and shear failure are those specified in the design code. Based on extensive numerical investigations, it may be positively stated that the optimum design of steel box girder bridges based on life-cycle cost approach proposed in this study provides a lot more rational and economical design, and thus the proposed approach will propose the development of new concepts and design methodologies that may have important implications in the next generation performance-based design codes and standards.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1995.10b
• /
• pp.131-138
• /
• 1995

A new technique using integer programming based on fuzzy multi-criteria function is proposed for generator maintenance scheduling. Minimization maintenance delay cost and maximization reserve power are considered for fuzzy multi-criteria function. To obtain an optimal solution for generator maintenance scheduling under fuzzy environment, fuzzy multi-criteria integer programming is used. In the maintenance scheduling, a characteristic feature of the presented approach is that the crisp constraints with uncertainty can be taken into account by using fuzzy set theory and so more flexible solution can be obtained. The effectiveness of the proposed approach is demonstrated by the simulation results.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.1
• /
• pp.20-28
• /
• 2016

This paper presents a generation rescheduling method for the enhancement of transient stability in power systems. The priority and the candidate generators for rescheduling are calculated by using the energy margin sensitivity. The generation rescheduling formulates the Lagrangian function with the fuel cost and emission such as NO_x and SO_x from power plants. The generation rescheduling searches for the solution that minimizes the Lagrangian function by using the Newton’s approach. While the Pareto optimum in the fuel cost and emission minimization has a drawback of finding a number of non-dominated solutions, the proposed approach can explore the non-inferior solutions of the multiobjective optimization problem more efficiently. The method proposed is applied to a 4-machine 6-bus system to demonstrate its effectiveness.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2002.05b
• /
• pp.829-836
• /
• 2002

The paper presents a multi-objective genetic algorithm approach to the design of a water distribution network. The objectives considered are minimization of network cost and maximization of a reliability measure. In this study, a new reliability measure, called network resilience, is introduced. This measure mimics a designer's desire of providing excess power at nodes and designing reliable loops with practicable pipe diameters. The proposed method produces a set of Pareto-optimal solutions in the search space of cost and network resilience. Genetic algorithms are observed to be poor in handling constraints. To handle constraints in a better way, a constraint handling technique that does not require a penalty coefficient and applicable to water distribution systems is presented. The present model is applied to two example problems, which were widely reported. Pipe failure analysis carried out on some of the solutions obtained revealed that the network resilience based approach gave better results in terms of network reliability.