Solving Multi-Mode Time-Cost-Quality Trade-off Problem in Uncertainty Condition Using a Novel Genetic Algorithm
International Journal of Management and Fuzzy Systems
Volume 3, Issue 3, June 2017, Pages: 32-40
Received: May 13, 2017;
Accepted: Jun. 14, 2017;
Published: Jul. 21, 2017
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Hasan Hosseini-Nasab, Industrial Engineering Department, Yazd University, Yazd, Iran
Masour Pourkheradmand, Industrial Engineering Department, Yazd University, Yazd, Iran
Naser Shahsavaripour, Department of Industrial Management, Vali-e-Asr University, Rafsanjan, Iran
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In this paper a Fuzzy Discrete Time-Cost-Quality Trade-off Problem (FDTCQTP), is presented. All of three main factors of a project are considered in uncertainty condition using fuzzy theory. Time, cost and quality are considered as fuzzy trapezoidal numbers and a novel Genetic Algorithm; Super Genetic Algorithm (SGA) is introduced to solve the problem. Project network paths are calculated via a new algorithm which it can be very useful for complex project networks and in order to comparing the fuzzy numbers, a new Fuzzy Number Ranking (FNR) method is introduced. The proposed algorithm is compared with classic GA by ANOVA, and the results demonstrate its efficiency. An applied example is used to more details.
Project Scheduling, Time-Cost-Quality Trade-off Problem, Metaheuristics, Genetic Algorithm, Fuzzy Theory, Fuzzy Number Ranking, CPM, ANOVA
To cite this article
Solving Multi-Mode Time-Cost-Quality Trade-off Problem in Uncertainty Condition Using a Novel Genetic Algorithm, International Journal of Management and Fuzzy Systems.
Vol. 3, No. 3,
2017, pp. 32-40.
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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