• IE interfaces
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• v.17 no.3
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• pp.282-293
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• 2004

Line Balancing is the problem to assign tasks to stations while satisfying some managerial viewpoints. Most researches about the Mixed-Model Line Balancing problems are focused on the minimizing the total processing time or the number of workstations. Independently, some research reports consider the balance issues of the physical workloads on the assembly line. In this paper, we are presenting a new mathematical model to accomplish the line balance considering both the processing time and the workloads at the same time. To this, end, we propose an zero-one integer program problem, and we use the Chebyshev Goal Programming approach as the solution method. Some computational test runs are performed to compare the pay-offs between the processing time and the workloads. And, the test results show us that the reliable balanced work schedules can be obtained through the proposed model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.2
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• pp.114-126
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• 2009

In this paper, a versatile multi-criteria optimization concept for fatigue life prediction is introduced. Multi-criteria 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.

• 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.