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A Multi-objective Stochastic Programming Approach For Project Time, Cost And Quality Trade-off Problem (tcqtp)

Submitted2016-09-05
Last Update2016-09-05
TitleA Multi-objective Stochastic Programming Approach For Project Time, Cost And Quality Trade-off Problem (tcqtp)
Author(s)Author #1
Author title:
Name: Behrooz Ahadian
Org: Department of Industrial Engineering, Najaf Abad Branch, Islamic Azad University, Isfahan, Iran
Country:
Email: Behrooz@gmail.com

Author #2
Author title:
Name: Omid Veisy
Org: Department of Industrial Engineering, Tehran University, Tehran, Iran
Country:
Email:

Author #3
Author title:
Name: Vahid Azizi
Org: Faculty of Industrial Engineering, Khajeh Nasir Toosi University of Technology, Tehran, Iran
Country:
Email:

Other Author(s)
Contact AuthorAuthor #1
Alt Email: ahadian.behrooz@gmail.com
Telephone:
KeywordsProject management, Chance-constrained compromise programming, Multiobjective programming, Time, cost and quality trade-off, Linear programming
AbstractGenerally, in project time, cost and quality trade-off problems, the decision maker (DM) has to take different conflicting objectives into account in order to find an optimal solution. In project management literature, many models have been developed for project crashing and project time-cost trade-off, but only a few of them consider quality as an objective. This article employs a chance constrained compromise programming approach (CCCP) to solve the time, cost and quality trade-off problem (TCQTP). The purpose of this paper is to present and test a new model for the project time, cost and quality problem. In fact, we try to find the optimal decrease in cost and duration of activities while maximizing quality under uncertainty conditions. In order to expect more realistic outcomes for the problem of uncertainties in project activities, time should be taken into account. Therefore, we assume the activity duration as a random and normally distributed parameter. An example of a project network, consisting of 6 nodes and 7 activities, is analyzed under different uncertainty levels.
Paperview paper 3718.pdf (312KB)

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