• Structural Engineering and Mechanics
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• v.3 no.4
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• pp.373-382
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• 1995

The weighting strategy has received a great attention and has been widely applied to multicriterion optimization. This gaper examines a global criterion method (GCM) with the weighting objectives strategy in fuzzy structural engineering problems. Fuzziness of those problems are in their design goals, constraints and variables. Most of the constraints are originated from analysis of engineering mechanics. The GCM is verified to be equivalent to fuzzy goal programming via a truss design. Continued and mixed discrete variable spaces are presented and examined using a fuzzy global criterion method (FGCM). In the design process a weighting parameter with fuzzy information is introduced into the design and decision making. We use a uniform machine-tool spindle as an illustrative example in continuous design space. Fuzzy multicriterion optimization in mixed design space is illustrated by the design of mechanical spring stacks. Results show that weighting strategy in FGCM can generate both the best compromise solution and a set of Pareto solutions in fuzzy environment. Weighting technique with fuzziness provides a more relaxed design domain, which increases the satisfying degree of a compromise solution or improves the final design.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.3
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• pp.47-61
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• 2007

This paper presents two elimination methods of subtours, which is obtained by applying the Out-of-Kilter algorithm to the sequential ordering problem (SOP) to produce a feasible solution for the SOP. Since the SOP is a kind of asymmetric traveling salesman problem (ATSP) with precedence constraints, we can apply the Out-of-Kilter algorithm to the SOP by relaxing the precedence constraints. Instead of patching subtours, both of two elimination methods construct a feasible solution of the SOP by using arcs constructing the subtours, and they improve solution by running 3-opt and 4-opt at each iteration. We also use a perturbation method. cost relaxation to explore a global solution. Six cases from two elimination methods are presented and their experimental results are compared to each other. The proposed algorithm found 32 best known solutions out of the 34 instances from the TSPLIB in a reasonable time.

• Journal of the Korean Society of Marine Environment & Safety
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• v.6 no.1
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• pp.23-33
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• 2000

This paper is concerned with finding the global optimal solutions for the redundancy optimization problems in series-parallel systems related with system safety. This study transforms the difficult problem, which is classified as a nonlinear integer problem, into a 0/1 IP(Integer Programming) by using binary integer variables. And the global optimal solution to this problem can be easily obtained by applying GAMS (General Algebraic Modeling System) to the transformed 0/1 IP. From computational results, we notice that GA(Genetic Algorithm) to this problem, which is, to our knowledge, known as a best algorithm, is poor in many cases.

• Journal of Korean Academy of Nursing Administration
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• v.23 no.2
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• pp.111-117
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• 2017

Getting evidence in to practice tends to focus on strategies, theories and studies that aim to close the gap between research knowledge and clinical practice. The evidence to practice gap is more about systems than individual clinician decision making. The absence of evidence for administration and management in the organization of healthcare is persistent. Teaching nurses and providing evidence as the solution to evidence-based healthcare is no longer axiomatic. Previous studies have concluded that unit level strategies integrate multi-professional teams with organizational needs and priorities. This 'best fit' approach that characterizes how healthcare is structured and delivered. The published literature shows that increased readiness for change is aligned with integrated approaches informed by conceptual models. The Joanna Briggs Collaboration is the largest global collaboration to integrate evidence within a theory informed model that brings together academic centres, hospitals and health systems for evidence synthesis, transfer and implementation. The best approaches to implementation are tailored to local culture and context, benchmark against international evidence, combine a theory informed model and stakeholder perspectives to improve the structure and processes of health care policy and practice.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.862-866
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• 2003

Traveling Salesman Problem(TSP) is a combinational optimization problem, Genetic Algorithm(GA) and Lin-Kernighan(LK) Heuristic［1］that is Local Search Heuristic are one of the most commonly used methods to resolve TSP. In this paper, we introduce ACS(Ant Colony System) Algorithm as another approach to solve TSP and propose a new pheromone updating method. ACS uses pheromone information between cities in the Process where many ants make a tour, and is a method to find a optimal solution through recursive tour creation process. At the stage of Global Updating of ACS method, it updates pheromone of edges belonging to global best tour of created all edge. But we perform once more pheromone update about created all edges before global updating rule of original ACS is applied. At this process, we use the frequency of occurrence of each edges to update pheromone. We could offer stochastic value by pheromone about each edges, giving all edges' occurrence frequency as weight about Pheromone. This finds an optimal solution faster than existing ACS algorithm and prevent a local optima using more edges in next time search.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.2
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• pp.406-414
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• 2002

A new approach, referred to as a successive zooming genetic algorithm (SZGA), is Proposed for identifying a global solution for continuous optimization problems. In order to improve the local fine-tuning capability of GA, we introduced a new method whereby the search space is zoomed around the design point with the best fitness per 100 generation. Furthermore, the reliability of the optimized solution is determined based on the theory of probability. To demonstrate the superiority of the proposed algorithm, a simple genetic algorithm, micro genetic algorithm, and the proposed algorithm were tested as regards for the minimization of a multiminima function as well as simple functions. The results confirmed that the proposed SZGA significantly improved the ability of the algorithm to identify a precise global minimum. As an example of structural optimization, the SZGA was applied to the optimal location of support points for weight minimization in the radial gate of a dam structure. The proposed algorithm identified a more exact optimum value than the standard genetic algorithms.

• Journal of Electrical Engineering and Technology
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• v.4 no.4
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• pp.457-466
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• 2009

This paper presents efficient parallel genetic algorithm (EPGA) based decomposed network for optimal power flow with various kinds of objective functions such as those including prohibited zones, multiple fuels, and multiple areas. Two coordinated sub problems are proposed: the first sub problem is an active power dispatch (APD) based parallel GA; a global database generated containing the best partitioned network: the second subproblem is an optimal setting of control variables such as generators voltages, tap position of tap changing transformers, and the dynamic reactive power of SVC Controllers installed at a critical buses. The proposed approach tested on IEEE 6-bus, IEEE 30-bus and to 15 generating units and compared with global optimization methods (GA, DE, FGA, PSO, MDE, ICA-PSO). The results show that the proposed approach can converge to the near solution and obtain a competitive solution with a reasonable time.

• Industrial Engineering and Management Systems
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• v.10 no.2
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• pp.123-127
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• 2011

Nowadays, green purchasing, stop global warming, love the mother earth, and others that related to environment become hot issues. Manufactures industries tend to more active and responsive to those issues by adopting green strategies or program like Environmentally Conscious Manufacturing (ECM). In this article, an electronic company had applied 12 ECM Program and tries to choose one of those programs using 6 criteria, such as total cost involved, quality, recyclable material, process waste reduction, packaging waste reduction, and regulation compliance. By using multi-criteria decision making model, i.e. Analytical Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Modified TOPSIS methods, the ECM Program 9 (Open pit) is the best option.

• Journal of Communications and Networks
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• v.5 no.3
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• pp.258-265
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• 2003

Transmission of continuous media streams has been a challenging problem of multimedia service. Lots of works have been done trying to figure out the best solution for this problem, and some works presented the optimal solution for transmitting the stored video using smoothing schemes applied to each individual stream. But those smoothing schemes considered only one stream, not the whole streams being serviced, to apply themselves, which could only achieve local optimum not the global optimum. Most of all, they did not exploit statistical multiplexing gain that can be obtained before smoothing. In this paper, we propose a new smoothing scheme that deals with not an individual stream but the whole streams being serviced simultaneously to achieve the optimal network bandwidth utilization and maximize the number of streams that can be serviced simultaneously. We formally proved that the proposed scheme not only provides deterministic QoS for each client but also maximizes number of clients that can be serviced simultaneously and hence achieves maximum utilization of transmission bandwidth.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.47-57
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• 2013

Big data analysis needs a new tool for decision making in view of data volume, speed, and variety. Many global IT enterprises are announcing a variety of Big data products with easy to use, best functionality, and modeling capability. Big data packages are defined as a solution represented by analytic tools, infrastructures, platforms including hardware and software. They can acquire, store, analyze, and visualize Big data. There are many types of products with various and complex functionalities. Because of inherent characteristics of Big data, selecting a best Big data package requires expertise and an appropriate decision making method, comparing the selection problem of other software packages. The objective of this paper is to suggest a decision making method for selecting a Big data package. We compare their characteristics and functionalities through literature reviews and suggest selection criteria. In order to evaluate the feasibility of adopting packages, we develop two Analytic Hierarchy Process(AHP) models where the goal node of a model consists of costs and benefits and the other consists of selection criteria. We show a numerical example how the best package is evaluated by combining the two models.