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논문 기본 정보

자료유형
학술대회자료
저자정보
Seren Ozmehmet Tasan (Waseda University) Mitsuo Gen (Waseda University)
저널정보
대한산업공학회 대한산업공학회 춘계공동학술대회 논문집 2008년 대한산업공학회 춘계공동학술대회 논문집
발행연도
2008.5
수록면
30 - 37 (8page)

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In a multiple project environment, where there also exists alternative ways for performing each project, a new type of problem called resource constrained multiple project scheduling problem with alternative projects (rcmPSP/aP) forms. The rc-mPSP/aP may be viewed as a network of projects which also involves project alternatives. When dealing with alternative projects, there are two approaches, i.e., hierarchic and the monolithic approach. Traditionally, almost all of the researchers are using hierarchic approach. The hierarchical approach partitions the problem into a hierarchy of two subproblems, i.e. alternative project selection and scheduling, where the first one tries to identify the best alternative among projects (simplifies the problem into a rc-mPSP) and then the second one tries to solve the rc-mPSP using only these alternative projects. Therefore, in this approach, since the researchers are eliminating some features of the whole problem before scheduling procedure, the problem in these academic researches is losing its integrity. In this research, we are planning to apply a monolithic approach which considers these two sub-problems together. The monolithic approach formulates the problem as an exclusive scheduling problem and tries to solve the rcmPSP/ aP. Particularly, a genetic algorithm (GA) approach will be constructed in order to solving rcmPSP/ aP efficiently. Since there exist two sub-problems in rc-mPSP/aP, a multistage GA is going to be constructed to reflect the sub-problems together in the exclusive problem. Finally, time and resource based objective functions are going to be used together to evaluate the performance of the proposed monolithic multistage GA approach.

목차

Abstract
1. Introduction
2. Combined Project Selection and Resource Constrained Multiple Project Scheduling Problem
3. Priority-based Multistage Genetic Algorithm for solving rc-mPSP/aP
4. Numerical Example
5. Conclusion
References

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UCI(KEPA) : I410-ECN-0101-2014-530-001434215