A Fuzzy Multi-objective Mathematical Programming Model for Project Management Decisions Considering Quality and Contractual Reward and Penalty Costs in a Project Network

2020 ◽  
Author(s):  
S. M. Hashemi ◽  
S. M. Mousavi ◽  
A. Patoghi
Keyword(s):  
Project Management ◽  
Mathematical Programming ◽  
Programming Model ◽  
Mathematical Programming Model ◽  
Management Decisions ◽  
Multi Objective ◽  
Penalty Costs ◽  
Project Network

Optimal project portfolio selection with reinvestment strategy considering sustainability in an uncertain environment: a multi-objective optimization approach

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammadali Zarjou ◽  
Mohammad Khalilzadeh
Keyword(s):  
Mathematical Programming ◽  
Portfolio Selection ◽  
Programming Model ◽  
Sustainability Indicators ◽  
Selection Problem ◽  
Project Portfolio ◽  
Mathematical Programming Model ◽  
Content Type ◽  
Multi Objective ◽  
Project Portfolio Selection

PurposeThis study aims to develop a model for project portfolio selection considering organizational goals such as budgets, sustainability cash flow and reinvestment strategy under an uncertain environment.Design/methodology/approachA multi-objective mathematical programming model is proposed for project selection, which takes the social, environmental and financial aspects into account as the objectives of the project portfolio selection problem. The project evaluation and selection process in one of the large capitals in the Middle East with numerous urban construction projects was considered as a real case study, in which the subjects of environmental and social sustainability are of great importance. Then, the most significant criteria for project evaluation and selection based on sustainability were identified and ranked using the fuzzy best-worst method (BWM).FindingsThe criterion of “defining clear and real objectives” was ranked first, “project investment return period” was ranked second, “minimum changes in the predicted range” was ranked third, and the other ten sustainability indicators were ranked as well. Next, the presented mathematical programming model was solved using the augmented e-constraint method. The sensitivity analysis indicated that increasing the amount of investments in projects would increase their net present value. Also, increased investment had no effect on sustainability, while decreased investment caused sustainability to not being optimal.Originality/valueThis study focuses on the impact of the amount of investments on projects, and the associated costs of sustainable projects. Further to the authors' knowledge, there has been no relevant study taking uncertainty into account. Also, very few studies proposed a mathematical programming model for the project portfolio selection problem. Moreover, this research uses the brainstorming and Delphi method to identify the sustainability indicators influencing the organization and screens the evaluation indicators. Furthermore, the weights of the evaluation indicators are determined using the fuzzy BWM based on the consistency of opinions.

scholarly journals A Model for IT/IS Project Portfolio Selection in the Presence of Uncertainty: Combination of Fuzzy Multi-Criteria Decision Making and Fuzzy Mathematical Programming

2012 ◽  
Vol 488-489 ◽  
pp. 411-416 ◽  
Author(s):  
Reihaneh Amel Sadeghi ◽  
Mehdi Seifbarghy
Keyword(s):  
Decision Making ◽  
Mathematical Programming ◽  
Portfolio Selection ◽  
Programming Model ◽  
Multi Criteria Decision Making ◽  
Project Portfolio ◽  
Fuzzy Mathematical Programming ◽  
Mathematical Programming Model ◽  
Multi Objective ◽  
Second Stage

IT/IS represents a substantial financial investment for many organizations. Making IT project portfolio decision is difficult, because long lead times of IT project and market and technology dynamics lead to unavailable and unreliable collected data for portfolio management. This uncertainty has been modeled using fuzzy concepts. We need a collective model that will help decision-makers evaluate potential new investment projects in an easy, cost-effective, and collective manner. Hence, we propose a new approach based on the fuzzy multi-criteria decision model (FMCDM) and a fuzzy binary multi-objective linear programming model, featuring a 2-stage evaluation and selection process with 19 criteria for IT/IS investment. At the first stage, evaluation, all stakeholders in a corporation can decide the relative weights they give to the criteria when they evaluate a new IT/IS project by using linguistic values. Experts can also use linguistic values to evaluate all candidates easily. Only an Excel worksheet is needed to obtain an evaluation result. The results of FMCDM of the aforementioned are treated as input of a fuzzy binary mathematical programming model as coefficients of objective functions, which is the second stage of the proposed model. In the second stage, selection, we have developed a fuzzy binary mathematical programming model in order to find an optimum combination of investment portfolio considering a multi-objective measurement function in three ways: to maximize the benefit, to maximize the confidence level and to minimize the cost of projects in a complete ambiguous condition, when their initial investment costs, profits, confidence levels, resource requirements and total available budgets are assumed to be uncertain. We solve it in Lingo 10.0 through a Branch and Bound algorithm. In this paper, for the first time we have developed a model for IT/IS project portfolio selection in presence of uncertainty that is combination of fuzzy multi-criteria decision making and fuzzy mathematical programming with 19 criteria that is compatible with the nature of IT projects. We conduct a case study to show how this model can be used and discuss the results.

scholarly journals Rank-Based Solution Methods and their Applications in Determination of Non-Dominated Points Set For A Multi-Objective Integer Programming Model

2020 ◽  
Vol 5 (6) ◽  
pp. 1249-1269
Author(s):  
Ali Al-Hasani ◽  
Masar Al-Rabeeah ◽  
Santosh Kumar ◽  
Andrew Eberhard
Keyword(s):  
Integer Programming ◽  
Mathematical Programming ◽  
Programming Model ◽  
Optimal Solution ◽  
Optimal Solutions ◽  
Mathematical Programming Model ◽  
Integer Programming Model ◽  
Multi Objective ◽  
Solution Methods ◽  
Single Objective

For any single-objective mathematical programming model, rank-based optimal solutions are computationally difficult to find compared to an optimal solution to the same single-objective mathematical programming model. In this paper, several methods have been presented to find these rank-based optimal solutions and based on them a new rank-based solution method (RBSM) is outlined to identify non-dominated points set of a multi-objective integer programming model. Each method is illustrated by a numerical example, and for each approach, we have discussed its limitations, advantages and computational complexity.

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