Fuzzy Mathematical Model For Optimizing Success Criteria Of Projects: A Project Management Application (original) (raw)
Related papers
2015 International Conference on Industrial Engineering and Operations Management (IEOM), 2015
Forecasting the progress or regression of a project can definitely change the project's direction and lead to implement a strategy with lower risks. In this paper a new technique is developed first in order to model the problem using Analytical Hierarchy Process as a Multi Criteria Decision Making and then to apply fuzzy theory in project management's main factors such as: time, quality and cost by defining the triangular fuzzy membership function for each one in the MATLAB fuzzy toolbox based on if-then rules extracted from the experts' experiences. This methodology can be used by project managers to reduce the risks of uncertainty when deciding for investments, resource allocation and other levels from planning to executing as well as easily determining the percent of performance. The contribution of this study lies in presenting a fuzzy mathematical programming methodology to fuzzy multi-objective PM decisions, and provides a systematic decision-making framework that facilitates the decision maker to interactively adjust the search direction until the preferred efficient solution is obtained.
Fuzzy multi-objective project selection problem using additive weighted fuzzy programming
In project selection (PS) problems, the decision makers usually consider objectives in the frame of multi-objective problems which are more consistent with decision making realities. In addition to, environment coefficients and related parameters are frequently fuzzy in nature. This paper focuses on developing an additive weighted fuzzy programming (AWFP) approach for solving the multi-objective PS decision problems in fuzzy environment. The proposed fuzzy PS here attempts to simultaneously maximize total project benefits while total risk and total cost must be minimized. Also a number of real-world constraints like logical and resources constraints are presented. In order to illustrate the proposed approach a numerical example is given. Computational results show that the proposed approach is very promising and achieves quality results efficiently to PS problems.
2013
Project managers are often facing the challenge of optimal allocation of resources to different project tasks involving different and usually conflicting objectives. The aim of this research is to simultaneously optimize the time, the cost, and the quality of a project by analyzing their trade-offs. To achieve this goal, the quality of a project task is first defined as a function of its time and cost. Then, a fuzzy rule-base is used to determine these functions more adequately. Next, the total project cost, the total project time, and the overall project quality are simultaneously optimized by a linear fuzzy multiobjective optimization model to decide the preferred mode of executing a task. An example is given at the end to show the applicability and the validity of the proposed methodology. Index Terms-Multi-objective optimization, project time, cost and quality, fuzzy rule-base, software projects.
Computers & Industrial Engineering, 2013
The aim of this paper is to develop an interactive two-phase method that can help the Project Manager (PM) with solving the fuzzy multi-objective decision problems. Therefore, in this paper, we first revisit the related papers and focus on how to develop an interactive two-phase method. Next, we establish to consider the imprecise nature of the data by fulfilling the possibilistic programming model, and we also assume that each objective work has a fuzzy goal. Finally, for reaching our objective, the detailed numerical example is presented to illustrate the feasibility of applying the proposed approach to PM decision problems at the end of this paper. Results show that our model can be applied as an effective tool. Furthermore, we believe that this approach can be applied to solve other multi-objective decision making problems.
Journal of Optimization in Industrial Engineering, 2016
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...
Project selection using fuzzy linear programming model
International Journal of Operational Research, 2014
In this paper, a fuzzy linear programming model is presented for selecting the proper project and obtaining budget at the end of tth period. The real world uncertainties are considered through fuzzy concepts and a linear programming model is proposed to model the uncertainty in data. The tax and depreciation are incorporated into the proposed model and the investments are considered as investment projects. The model allows considering different rate of return for each project. Finally, to illustrate the application of the proposed model, a numerical example is solved.
Computers & Industrial Engineering, 2015
Project management decisions require considering several conflicting constraints and objectives as well as uncertainties in the information over the planning period. The study aims to design a multi-objective linear programming model for solving project network problem under fuzzy environment. The developed model consists of three objectives such as minimizing total project completion time, minimizing total project completion cost and minimizing the earliest time of an event requiring special attention by taking into account several factors such as crash time, normal time, normal cost, crash cost, indirect cost as well as financial bonus and incremental penalty cost. In the study, a case study based on a real life problem is conducted to illustrate the validity and feasibility of the model. The study contributes to the project network literature by developing the fuzzy goal programming model and allows the project managers simultaneously evaluate financial bonus and incremental penalty cost with respect to total project time. In addition, the results of the sensitivity analysis highlight that the developed model can be used for helping the contractors make effective decisions.
Using fuzzy decision making for the evaluation of the project management internal efficiency
Decision Support Systems, 2006
Specific applications of fuzzy logic in project management are relatively few in comparison to other application areas. The criteria of project cost, project time, and project quality may be considered as project management internal measures of efficiency. The objective of this research is to present an approach that employs fuzzy decision making (FDM) to combine these three measures into one measure namely the project management internal efficiency (PMIE) which should represent an overall estimate of how well the project was managed and executed. The proposed approach for the evaluation of PMIE is illustrated on a case study. A fuzzy decision making system is designed and implemented using the MATLAB software for the evaluation of the PMIE. The methodology and procedure proposed in this research may be easily implemented by project management organizations. The evaluation of PMIE can serve for project managers and for project organizations as an indicator for the level of achievement of the project management internal objectives. PMIE may help in the evaluation of the performance of project teams.
A Fuzzy Approach for Measuring Project Performance Based on Relative Preference Relation
Industrial Engineering & Management Systems, 2017
Earned Duration Management (EDM) is the most recent methodology for project management that unlike former techniques, measures project performance using time-based data, In contrast to former techniques. This difference generates more realistic consequences in performance estimation and measurement. The novel approach which has been proposed in this paper aims to measure project performance by applying EDM techniques under uncertain conditions based on fuzzy theory. In this regard, we applied linguistic terms to express activities' progress and developed EDM metrics to fuzzy performance and estimation indices which are capable of measuring performance under uncertain condition. In order to rank fuzzy numbers, a new method based on relative preference relation has been used, which has been clarified by a real sample case in road construction projects.
A multiobjective fuzzy model for selecting and planning a project portfolio in a public organisation
International Journal of Engineering Management and Economics, 2015
Our purpose in this paper is to assist decision-makers in the task of selecting project portfolios to satisfy their requirements and guarantee profitable growth. This task usually involves decision-makers having to face multiple objectives and constraints, as well as the uncertainty associated with certain parameters of the problem. Therefore, in this paper, we propose a multiobjective programming model, which includes uncertainty through the use A multiobjective fuzzy model for selecting and planning a project portfolio 49 of fuzzy parameters and allows us to represent information not fully known by the decision-makers. The resulting model has been applied to a project portfolio selection process in a public organisation.