1Department of Industrial & Production Engineering, Rajshahi University of Engineering & Technology.
2Assistant Professor, Department of Industrial and Production Engineering, Rajshahi University of Engineering and Technology, Bangladesh
3Professor, Department of Industrial and Production Engineering, Rajshahi University of Engineering and Technology, Bangladesh
Abstract
Smooth implementation and controlling conflicting goals of a project with the usage of all related resources through organization is inherently a complex task to management. At the same time deterministic models are never efficient in practical project management (PM) decision problems because the related parameters are frequently fuzzy in nature. The project execution time is a major concern of the involved stakeholders (client, contractors and consultants). For optimization of total project cost through time control, here crashing cost is considered as a critical factor in project management. The proposed approach aims to formulate a multi objective linear programming model to simultaneously minimize total project cost, completion time and crashing cost with reference to direct, indirect cost in the framework of the satisfaction level of decision maker with fuzzy goal and fuzzy cost coefficients.. To make such problems realistic, triangular fuzzy numbers and the concept of minimum accepted level method are employed to formulate the problem. The proposed model leads decision makers to choose the desired compromise solution under different risk levels and the project optimization problems have been solved under multiple uncertainty conditions. The Analytical Hierarchy Process is used to rank multiple objectives to make the problem realistic for the respective case. Here minimum operator and AHP based weighted average operator method is used to solved the model and the solution is obtained by using LINGO software
Highlights
A multi-objective linear programming model is developed to minimize total project cost, completion time and crashing cost
The model is given with reference to direct, indirect cost in the framework of the satisfaction level of decision maker with fuzzy goal and fuzzy cost coefficients
Analytical Hierarchy Process is used to rank multiple objectives
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