Fuzzy Multi-Objective Linear Programming for Project Management Decision under Uncertain Environment with AHP Based Weighted Average Method

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 to the involved stakeholders (client, contractors and consultants). For optimization of total project cost through time control, crashing cost is considered here as a critical factor. The proposed approach aims to formulate a multi objective linear programming model to simultaneously minimize the total project cost, completion time and crashing cost within 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 (AHP) is used to rank the multiple objectives to make the problem realistic for the respective case. Here minimum operator method and AHP based weighted average operator method is used to solved the model and the solution is obtained by using LINGO software

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