• Journal of Korea Society of Industrial Information Systems
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• v.6 no.2
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• pp.63-73
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• 2001

An alternative approach to formulating a special class of linear goal programming (LGP) models is presented. We propose a formulation of the LGP model that can include the decision variables in the objective function. We specifically propose that the position of the decision variables in the objective function be used to eliminate goal constraints whose sole purpose is to indirectly optimize decision variables. For the select group of LGP problems wherever indirect optimization of decision variables are sought, the alternative LGP model formulation is able to reduce the size of these LGP models and in turn the computational effort required for their solution.

• Journal of the military operations research society of Korea
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• v.7 no.2
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• pp.63-99
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• 1981

The generalized goal decomposition model proposed by Ruefli as a single period decision model is presented for the purpose of a review and extended to make a multiple period planning model. The multiple period planning model in the three level organization is formulated with, linear goal deviations by introducing the goal programming method. Dynamic formulation using the generalized goal decomposition model for each single period problem is also presented. An iterative search algorithm is presented as an appropriate solution method of the dynamic formulation of the multiple period planning model.

• Journal of the military operations research society of Korea
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• v.32 no.2
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• pp.21-39
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• 2006

This paper presents a mixed linear and integer goal programming (GP) model to aid in strategic planning and scheduling of guard soldiers. The proposed model is a general-purpose model, hence can be used to produce an optimal schedule with respect to any user-provided combination of guard post objectives and soldier preferences. We extensively test the usefulness of the model on a real-life dataset from a guard post in the ROK Army with using three objectives set by the guard post and three preferences provided by individual solders. Numerical results and analysis from these experiments show that the proposed guard scheduling model efficiently as well as effectively generates an optimal guard schedule and can also be used for an optimal revision of any existing schedule. In summary, these illustrate that the proposed model can be practically used for optimal planning and scheduling of guard soldiers in guard posts.

• Journal of The Korean Association of Information Education
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• v.19 no.2
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• pp.225-232
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• 2015

The goal of this study is to assess the effects of Scratch programming classes on preservice teachers by using computational thinking and cognitive evaluations based on Bloom's taxonomy. To pursue this research goal we measured preservice teachers' programming skills using cognitive evaluation items based on Bloom's taxonomy after preservice teachers took one-semester Scratch programming course. In addition, a survey focused on computational thinking (CT) concepts, CT practices, and CT perspectives was conducted. We also conducted artifact-based interviews to unpack preservice teachers' experiences of working on team projects and analyzed their experiences qualitatively. The results of this study are meaningful because we assessed preservice teachers' experiences comprehensively with both quantitative and qualitative methods. In addition, this study provides us with implications for evaluation perspectives in designing programming courses for preservice teachers by adopting Bloom's taxonomy scheme.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.43-54
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• 2005

For the effective design of automated distribution center composed of Automated Storage/Retrieval System, Automated Guided Vehicle System, and Conveyor System, we proposed an analysis method to determining. design and control parameters with multiple performance objectives using Compromise Programming, which can resolve the dilemma of conflicting objectives. The Evolution Strategy generates the optimal solutions for each objectives. The Analytic Hierarchy Process selects the best solution among the alternatives generated from Evolution Strategy. The Regression Analysis formulates the objective functions for each objectives. By reducing deviations between goal values and target values generated from Analytic Hierarchy Process, Compromise Programming determines design and control parameters by compromising the multiple objectives formulated using Regression Analysis. When the parameters of system are changed, this proposed analysis method has a benefit of reducing costs and time without repeating whole simulation run.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11A
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• pp.1079-1085
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• 2007

This Paper Proposes a new optimization algorithm named by GBNSGA-II(Goal-pareto Based Non-dominated Sorting Genetic Algorithm-II) which uses Goal Programming to find non-dominated solutions in NSGA-II. Although the conventional NSGA is very popular to solve multiobjective optimization problem, its high computational complexity, lack of elitism and difficulty of selecting sharing parameter have been considered as problems to be overcome. To overcome these problems, NSGA-II has been introduced as the alternative for multiobjective optimization algorithm preventing aforementioned defects arising in the conventional NSGA. Together with advantageous features of NSGA-II, this paper proposes rather effective optimization algorithm formulated by purposely combining NSGA-II algorithm with GP (Goal Programming) subject to satisfying multiple objectives as possible as it can. By conducting computer simulations, the superiority of the proposed GBNSGA-II algorithm will be verified in the aspects of the effectiveness on optimization process in presence of a priori constrained goals and its fast converging capability.

• Bulletin of the Society of Naval Architects of Korea
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• v.25 no.1
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• pp.11-20
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• 1988

From the engineering point of view, a synthesis as well as an analysis technique is explored to search for the improved design of grillage which is common in ship structure. As an approximate analysis method for the grillage, an interaction reaction method is developed and compared with the finite element method. It is found that the discrepancy between these two methods is so negligible that the percent method could be used effectively for the grillage analysis. As an optimization technique, a feasible direction method could be used is combined with the intersection reaction method in order to design a minimum weight optimal grillage. The feasible direction method shows a good numerical performance although it requires more calculation times compared with the direct search method. Finally, the application of multiple objective optimization method to grillage is investigated in order to resolve conflicts existed between the multiple objectives which is a common characteristic of structure design problem. Goal programming method is extended to handle a nonlinear property of constraints and objective functions. It seems that the nonlinear goal programming could help not only to establish a relative importance of each objective, but also enable the designer to choose the best combination of design variables.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.49-55
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• 2021

This study analyzed the relationship between the characteristics of learners and the achievement level according to the language they learn in programming education for non-major students. The learner's characteristics were set as mastery goal, situaltional interest, cognitive engagement, and self-efficacy for performance, and path analysis was conducted to understand the relationship between the language used and the learning achievement. Situaltional interest and cognitive engagement were found to have an effect on self-efficacy for performace, and self-efficacy for performance had an effect on academic achievement. At this time, the type of programming language to be studied showed a moderating effect on learning achievement. Based on the results of this study, it is suggested that appropriate instruction is needed for each language used in programming lessons for software non-majors.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.119-131
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• 1988

Vehicle Scheduling Problem (VSP) is a generic name given to a whole class of problems involving the visiting of "stations" by "vehicles," where a time is associated with each activity. The studies performed to date have the common feature of a single objective while satisfying a set of restrictions and known customer supplies or demands. However, VSPs may involve relevant multiple objectives and probabilistic supplies or demands at stations, creating multicriteria stochastic VSPs. This paper proposes a heuristic algorithm based on goal programming approach to schedule the most satisfactory vehicle routes of a bicriteria VSP with probabilistic supplies at stations. The two relevant objectives are the minimization of the expected travel distance of vehicles and the minimization of the due time violation for collection service at stations by vehicles. The algorithm developed consists of three major stages. In the first stage, an artificial capacity of vehicle is determined, on the basis of decision maker's subjective estimates. The second one clusters a set of stations into subsets by applying an efficient cluster method developed. In the third one, the stations in each subset are scheduled by applying an iterative goal programming heuristic procedure to each cluster.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.1
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• pp.1-10
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• 2001

As computer power is increased, refined finite element models are employed for structural analysis. However, it is difficult and expensive to use refined models in the design stage. The refined models especially cause problems in the preliminary design where the design is frequently changed. Therefore, simplified models are needed. The simplification process is regarded as an empirical technique. Simplified and equivalent finite element model of a structure has been studied and used in the preliminary design. A general approach to establish the simplified and equivalent model is presented. The generated simple model has satisfactory correlation with the corresponding refined finite element model. An optimization method, the Goal Programming algorithm is used to make the simple model. The simplified model is used for the design change and the changed design is recovered onto the original design. The presented method was verified with three examples.