• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1187-1192
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• 2008

In this paper, a versatile multi-objective optimization concept for fatigue life prediction is introduced. Multi-objective decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

• Journal of Korean Association for Spatial Structures
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• v.3 no.2 s.8
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• pp.77-83
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• 2003

This paper presents decision making method of structural multi-objective fuzzy optimum problem. The data and behavior of many engineering systems are not know precisely and the designer is required to design the system in the presence of fuzziness in the multi-goals, constraints and consequences of possible actions. In this paper, in order to find a satisfactory solution, the membership functions are constructed for the fuzzy objectives subject to the fuzzy constraints, and two approaches are presented by using the different types of fuzzy decision making. Thus, multi-objective fuzzy optimum problem can be converted into single objective non-fuzzy optimum problem and satisfactory solution of the multi-objective fuzzy optimum problem can be found with general optimum programming. Illustrative numerical example of the ten bar truss for minimum weight and minimum deflection is provided to demonstrate the process of finding the solution and the results are discussed.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.3
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• pp.44-50
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• 2017

This paper proposes arrival scheduling and advisory generation algorithms which can be used in the terminal airspace with Point-Merge procedures. The proposed scheduling algorithm consists of two steps. In the first step, the algorithm computes aircraft schedules at the entrance of the Point-Merge sequencing legs based on First-Come First-Served(FCFS) strategy. Then, in the second step, optimal sequence and schedules of all aircraft at the runway are computed using Multi-Objective Dynamic Programming(MODP) method. Finally, the advisories that have to be provided to the air traffic controllers are generated. To demonstrate the proposed algorithms, the simulation was conducted based on Jeju International Airport environments.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.10
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• pp.584-592
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• 2003

This paper presents a fuzzy-GA method for the allocation and operation of dispersed generator systems(DGs) based on load model in composite distribution systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load. The problem formulation considers an objective to reduce power loss of distribution systems and the constraints such as the number or total capacity of DGs and the deviation of the bus voltage. The main idea of solving fuzzy goal programming is to transform the original objective function and constraints into the equivalent multi-objectives functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm. The method proposed is applied to IEEE 12 bus and 33 bus test systems to demonstrate its effectiveness. .

• IE interfaces
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• v.16 no.4
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• pp.485-495
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• 2003

This paper reports on the application of the integration of mathematical programming model and database in a decision support system (DSS) for the planning of the multi-reservoir operating system. The DSS is based on a multi-objective, mixed-integer goal programming (MIGP) model, which can generate efficient solutions via the weighted-sums method (WSM). The major concern of this study is seamless, efficient integration between the mathematical model and the database, because there are significant differences in structure and content between the data for a mathematical model and the data for a conventional database application. In order to load the external optimization results on the database, we developed a systematic way of naming variable/constraint so that a rapid identification of variables/constraints is possible. An efficient database structure for planning of the multi-reservoir operating system is presented by taking advantage of the naming convention of the variable/constraint.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.30-35
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• 2013

Motivated by the emergency scheduling in a transportation network, this paper considers a transportation problem, in which, the truck times and transportation costs are assumed as uncertain variables. To meet the demand in the practical applications, two optimization objectives are considered, one is the total costs and another is the completion times. And then, a multi-objective optimization model is developed according to the situation in applications. Because there are commensurability and conflicting between the two objectives commonly, a solution does not necessarily exist that is best with respective to the two objectives. Therefore, the problem is reduced to a single objective model, which is an uncertain programming with a chance-constrain. After some analysis, its equivalent deterministic form is obtained, which is a nonlinear programming. Based on a stepwise optimization strategy, a solution method is developed to solve the problem. Finally, the computational results are provided to demonstrate the effectiveness of our model and algorithm.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05b
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• pp.237-243
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• 1997

The ultimate object of our study is to minimize the release of radioactive material into the environment and to maximize the treatable amount of the generated wastes. In planning the practical operation of the system, however, the operating cost, Process economics and technical flexibility must also be considered. For dealing with these multiple criteria decision making Problems, we used a foal programming which is a kind of multi-objective linear programming. This method requires the decision maker to set goals for each objective that one wishes to attain.

• Journal of Korean Society for Quality Management
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• v.24 no.1
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• pp.20-31
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• 1996

A pure zero-one integer program is formulated for determining where to assign the inspection stations in a multi-stage production system. The objective fuction is formulated to minimize the overall inspection costs. One of the major characteristics of this system is that an assigned inspection station is to inspect only the items produced in previous manufacturing stages. Each inspection station can be assigned to any possible inspection stage between two manufacturing stages. Error-free and screening inspection policy is assumed in this system and the defective items found in any inspection station will be reworked at once. The integer programming model presented in this paper has the advantages in the ease of modeling and modifiing as compared with the existing dymanamic programming methods. The solutions of the model can be easily obtained by the commercially available softwares like LINDO and GAMS.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.17-23
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• 2008

In this research article, scheduling a casting sequence in a job-shop type foundry involving a variety of casts made of an identical alloy but with different shapes and II weights, has been investigated. The objective is to produce the assigned mixed orders satisfying due dates and obtaining the highest ingot efficiency simultaneously. Implementing simple integer programming instead of complicated genetic algorithms accompanying rigorous calculations proves that it can provide a feasible solution with a high accuracy for a complex, multi-variable and multi-constraint optimization problem. Enhancing the ingot efficiency under the constraint of discrete ingot sizes is accomplished by using a simple and intelligible algorithm in a standard integer programming. Employing this simple methodology, a job-shop type foundry is able to maximize the furnace utilization and minimize ingot waste.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.146-153
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• 2004

This paper presents the method for the placement and operation of dispersed generator systems(DGs) using fuzzy goal programming in distribution systems. For the placement and operation of DGs the problem is formulated with reduction of search spaces and flexibility of system situations. Especially, the original objective function and constraints are transformed by fuzzy goal programming to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm.