• Journal of Korean Port Research
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• v.13 no.1
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• pp.27-40
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• 1999

This study aims to apply and examine the stochastic approach for empty container repositioning and leasing problem. For this a case study has been carried out on actual data such as various cost components and traffic flow. The results reveal that the proposed methodology produces more realistic results than the conventional deterministic approaches. It is also found that the results are significantly affected by the accuracy of demand and supply forecast.

• Korea Real Estate Review
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• v.28 no.1
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• pp.23-37
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• 2018

The genetic algorithm (GA) and branch and bound (B&B) methods are the useful methods of searching the optimal project combination (combinatorial optimization) to maximize the project effect considering the budget constraint and the balance of regional development with regard to the Urban Regeneration New Deal policy, the core real estate policy of the Moon Jae-in government. The Ministry of Land, Infrastructure, and Transport (MOLIT) will choose 13 central-city-area-type projects, 2 economic-base-type projects, and 10 public-company-proposal-type projects among the numerous projects from 16 local governments while each government can apply only 4 projects, respectively, for the 2017 Urban Regeneration New Deal project. If MOLIT selects only those projects with a project effect maximization purpose, there will be unselected regions, which will harm the balance of regional development. For this reason, an optimization model is proposed herein, and a combinatorial optimization method using the GA and B&B methods should be sought to satisfy the various constraints with the object function. Going forward, it is expected that both these methods will present rational decision-making criteria if the central government allocates a special-purpose-limited budget to many local governments.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1681-1693
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• 1997

In a distributed system, the simple file allocation problem determines the placement of copies of a file, so as to minimize the operating costs. The simple file allocation problem assumes the cost parameters to be fixed. In practice, these parameters change over time. In this research, dynamic file allocation problem for both single and multiple files are considered, which account for these changing parameters. A model for dynamic file allocation problem is formulated as a mixed integer program for which Lagrangian relaxation based branch-and-bound algorithm is developed. This algorithms is implemented and its efficiency is tested on medium to large test problems.