Abstract
The selection of project portfolio is the main problem in project-based organizations. In project selection, optimized decision to maximizing utilization of limited resources and achieving organizational goals by considering restrictions are important. Therefore, to facilitate project portfolio selection ...
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The selection of project portfolio is the main problem in project-based organizations. In project selection, optimized decision to maximizing utilization of limited resources and achieving organizational goals by considering restrictions are important. Therefore, to facilitate project portfolio selection in project-based organizations, an efficient model is proposed that is able to consider limitations, goals, and priorities of the organization in selecting the optimal combination of projects. The proposed model is a hybrid and flexible one which, including four main steps. First, with initial screening, to save time and money by using non-compensatory method, some of the poor candidate options are deleted. Then, due to multi-criteria nature of the problem, qualitative and quantitative criteria, and uncertainty of data in real world, the projects are ranked using fuzzy analytic hierarchy processes and uncertain judgments of decision-makers. To generate project baskets, integer linear programming (ILP), backpack model, is employed modifying the coefficients of the objective function of each project to preserve multi-criteria rating of projects, and then evaluate and rank the baskets. To validate the proposed model, we have carried out selection of project portfolio in the oil refining industry.
Hamidreza Shahabifard; Behrouz Afshar-nadjafi
Abstract
In this paper, a mathematical model is proposed for project portfolioselection and resource availability cost problem to scheduling activities inorder to maximize net present value of the selected projects preservingprecedence and resource constraints. Since the developed model belongs toNP-hard problems ...
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In this paper, a mathematical model is proposed for project portfolioselection and resource availability cost problem to scheduling activities inorder to maximize net present value of the selected projects preservingprecedence and resource constraints. Since the developed model belongs toNP-hard problems list, so a genetic based meta-heuristic algorithm isproposed to tackle the developed model. In the proposed algorithm besidecommon operators of genetic algorithms such as crossover & mutation, someintelligent operators are utilized for local search in computed resources andshifting the activities with negative cash flows. The key parameters of thealgorithm are calibrated using Taguchi method to accelerate convergence ofthe proposed algorithm. Then, the algorithm is used to solve 90 testproblems consisting 30 small-scale, 30 middle-scale and 30 large scaleproblems to examine the algorithm’s performance. It is observed that, insmall problems, the obtained solutions from the proposed genetic algorithmhave been comparably better than the local optimum solutions stemmedfrom Lingo software. On the other hand, for the middle and large sizeproblems which there is no local optimum available within the limited CPUtime, robustness of the proposed algorithm is appropriate
Abas Fadaei; Masood Rabieh; Mostafa Zandieh
Abstract
Considering that the active companies in the field of oil, gas,petrochemical and other energies are project-based and also theincrease of gas applicants who have taken policy of replacing the gasinstead of other fossil fuels, have imposed certain condition onorganizations and project managers in the ...
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Considering that the active companies in the field of oil, gas,petrochemical and other energies are project-based and also theincrease of gas applicants who have taken policy of replacing the gasinstead of other fossil fuels, have imposed certain condition onorganizations and project managers in the Gas Company.One of themost important problem in the issue of project management is projectportfolio selection which is defined one of the most importantactivities in many organization such as gas organization. In this studyat first the effective indicators on projects are extracted by using theliterature and interviews with the experts of gas industry then themathematical robust multi objective model is provided by consideringthe uncertainty and unreliability in some parameters of model. Thismodel is solved by using Non-dominate Sorting Genetic Algorithmfor 20 degree of risk-taking decision Gama ( , Ct Bt ).At the end forhelping in decision making the TOPSIS technique is used forproviding a specific answer in Pareto Front .
