• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.59-65
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• 1992

A modified primal-dual affine scaling algorithm for linear programming is presented. This modified algorithm generates an elipsoid containing all optimal dual solutions at each iteration, then checks whether or not a dual hyperplane intersects this ellipsoid. If the dual hyperplane has no intersection with this ellipsoid, its corresponding column must be optimal nonbasic. By condensing these columns, the size of LP problem can be reduced.

• Journal of the Chungcheong Mathematical Society
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• v.30 no.1
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• pp.31-40
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• 2017

In this paper, we consider a nonsmooth multiobjective robust optimization problem with more than two locally Lipschitz objective functions and locally Lipschitz constraint functions in the face of data uncertainty. We prove a nonsmooth sufficient optimality theorem for a weakly robust efficient solution of the problem. We formulate a Wolfe type dual problem for the problem, and establish duality theorems which hold between the problem and its Wolfe type dual problem.

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.2
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• pp.36-41
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• 1987

This paper presents a heuristic algorithm for solving the simple facility location problem. Its main procedure is essentially of 'add' type, which progressively selects facilities to open according to a certain criterion derived from the analysis of the linear programming dual. Computational experience with test problem from the literature is presented.

• Journal of Korean Institute of Industrial Engineers
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• v.10 no.2
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• pp.37-43
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• 1984

For the polymatroidal network, which has set-constraints on arcs, solution procedures to get the weighted maximal flows are investigated. These procedures are composed of the transformation of the polymatroidal network flow problem into a polymatroid intersection problem and a polymatroid intersection algorithm. A greedy polymatroid intersection algorithm is presented, and an example problem is solved. The greedy polymatroid intersection algorithm is a variation of Hassin's. According to these procedures, there is no need to convert the primal problem concerned into dual one. This differs from the procedures of Hassin, in which the dual restricted problem is used.

• Korean Management Science Review
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• v.29 no.1
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• pp.89-99
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• 2012

In this paper, we deal with the dual-depot heterogeneous vehicle routing problem with simultaneous delivery and pick up(DH-VRPSDP) in reverse logistics. The DH-VRPSDP is a problem of designing vehicle routes in a day of given vehicle to minimize the sum of fixed cost and variable cost over the planning horizon. Each customer can be visited only once according to the service combinations of that customer. Due to the complexity of the problem, we suggest a heuristic algorithm in which an initial solution is obtained by changing the customer and the vehicle simultaneously and then it is improved. A performance of the proposed algorithm was compared to both well-known results and new test problems.

• Communications for Statistical Applications and Methods
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• v.22 no.2
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• pp.137-146
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• 2015

Singh (2013) considered the dual problem to the calibration of design weights to obtain a new generalized linear regression estimator (GREG) for the finite population total. In this work, we have made an attempt to suggest a way to use the dual calibration of the design weights in case of multi-auxiliary variables; in other words, we have made an attempt to give an answer to the concern in Remark 2 of Singh (2013) work. The same idea is also used to generalize the GREG estimator proposed by Deville and S$\ddot{a}$rndal (1992). It is not an easy task to find the optimum values of the parameters appear in our approach; therefore, few suggestions are mentioned to select values for such parameters based on a random sample. Based on real data set and under simple random sampling without replacement design, our approach is compared with other approaches mentioned in this paper and for different sample sizes. Simulation results show that all estimators have negligible relative bias, and the multivariate case of Singh (2013) estimator is more efficient than other estimators.

• Journal of Family Resource Management and Policy Review
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• v.23 no.4
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• pp.23-39
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• 2019

This study aimed to explore the moderating effect of family strengths on the effect of work-family conflict on happiness in dual-income married couples. This study included 316 married employees who live in Seoul and have children attending junior high or lower grade schools. A survey was conducted December 1-30, 2018 by distributing questionnaires to child care centers, kindergartens, schools, companies, religious institutions, and other locations. The results are follows. First, in this study, the degree of family→work conflict was higher than that of work→family conflict in dual-income married couples, indicating that role conflict at work is greater due to family role pressures. Second, among the socio-demographic characteristics of dual-career couples, monthly income, family→work conflict (an independent variable), and family problem-solving skills (a moderating variable; a subcategory of family strengths) had a significant impact. In the analysis of the effect of work-family conflict on happiness, the higher the monthly income, the lower the family→work conflict, and the higher the family problem solving ability, the higher the feeling of happiness among dual-income married couples. When the work role conflicts from family life roles were more highly perceived in dual-income married couples. Moreover, family→work conflict and an interaction term of family problem-solving ability were identified as variables that had significant effects on happiness. Third, family problem-solving ability was identified as a moderator buffering the effect of work-family conflict on happiness.

• Journal of Engineering Education Research
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• v.23 no.6
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• pp.17-26
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• 2020

In this paper, the effect of daily creativity of engineering students on problem-solving ability is addressed through the dual mediating effect of teamwork competency and self-directed learning ability. To this end, a regression-based statistical mediation analysis has been performed on the dual mediation model in which daily creativity and problem solving ability were treated as independent and dependent variables respectively, and teamwork competence and self-directed learning ability were included as mediation variables. The analysis result confirmed that the daily creativity has direct effect on the problem-solving ability, as well as indirect effects through teamwork competence and self-directed learning ability. In particular, the serial mediating effect of teamwork competency and self-directed learning ability was also confirmed to be statistically significant in the relationship between daily creativity and problem-solving ability. This verifies that problem-solving ability can be improved not only directly by improving daily creativity but also indirectly by improving teamwork competence and self-directed learning ability. In addition, teamwork competency showed greater indirect effect on problem-solving ability than self-directed learning ability, so increasing teamwork competency has a more significant effect on improving problem-solving ability than increasing self-directed learning ability. Therefore, in order to develop better problem-solving ability, it is necessary to identify and improve the learners' teamwork competency first and to strive to create an environment where learners can solve problems based on mutual trust with their teammates.

• East Asian mathematical journal
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• v.27 no.5
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• pp.539-543
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• 2011

In this paper, we consider an optimization problem which consists a nonconvex quadratic objective function and two nonconvex quadratic constraint functions. We formulate its dual problem with semidefinite constraints, and we establish weak and strong duality theorems which hold between these two problems. And we give an example to illustrate our duality results. It is worth while noticing that our weak and strong duality theorems hold without convexity assumptions.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.254-261
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• 1998

This study presents a discrete optimization of tall steel buildings under multiple drift constraints using a dual method. Dual method can replace the primary optimization problem with a sequence of approximate explicit subproblems. Since each subproblem is convex and separable, it can be efficiently solved by using a dual formulation. Specifically, this study considers the discrete-optimization problem due to the commercial standard steel sections to select member sizes. The results by the proposed method will be compared with those of the conventional optimality criteria method