Proposal and Solution of a Mixed-Integer Nonlinear Optimization Model That Incorporates Future Preparedness for Project Portfolio Selection

2019 ◽  
pp. 1-13
Author(s):  
Taise C. L. Albano ◽  
Edmea C. Baptista ◽  
Fabiano Armellini ◽  
Daniel Jugend ◽  
Edilaine M. Soler
Keyword(s):  
Nonlinear Optimization ◽  
Portfolio Selection ◽  
Optimization Model ◽  
Mixed Integer ◽  
Project Portfolio ◽  
Project Portfolio Selection ◽  
Mixed Integer Nonlinear Optimization

scholarly journals A TYPE-2 FUZZY OPTIMIZATION MODEL FOR PROJECT PORTFOLIO SELECTION AND SCHEDULING INCORPORATING PROJECT INTERDEPENDENCY AND SPLITTING

2021 ◽  
Vol 27 (2) ◽  
pp. 493-510
Author(s):  
Samaneh Zolfaghari ◽  
Seyed Meysam Mousavi ◽  
Jurgita Antuchevičienė
Keyword(s):  
Portfolio Selection ◽  
Optimization Model ◽  
Fuzzy Optimization ◽  
Project Portfolio ◽  
Time Value Of Money ◽  
Solution Approach ◽  
Project Portfolio Selection ◽  
The Interest Rate ◽  
Interval Type

This paper presents a new optimization model and a new interval type-2 fuzzy solution approach for project portfolio selection and scheduling (PPSS) problem, in which split of projects and re-execution are allowable. Afterward, the approach is realized as a multi-objective optimization that maximizes total benefits of projects concerning economic concepts by considering the interest rate and time value of money and minimizes the tardiness value and total number of interruptions of chosen projects. Besides, budget and resources limitation, newfound relations are proposed to consider dependency relationships via a synergy among projects to solve PPSS problem hiring interval type-2 fuzzy sets. For validation of the model, numerical instances are provided and solved by a new extended procedure based on fuzzy optimistic and pessimistic viewpoints regarding several situations. In the end, their results are studied. The results show that it is more beneficial when projects are allowed to be split.

Mixed-integer nonlinear optimization for district heating network expansion

2020 ◽  
Vol 68 (12) ◽  
pp. 985-1000
Author(s):  
Marius Roland ◽  
Martin Schmidt
Keyword(s):  
Nonlinear Optimization ◽  
Optimization Model ◽  
Thermal Effects ◽  
Nonlinear Models ◽  
Valid Inequalities ◽  
Average Power ◽  
District Heating ◽  
Mixed Integer ◽  
Mixed Integer Nonlinear Optimization

AbstractWe present a mixed-integer nonlinear optimization model for computing the optimal expansion of an existing tree-shaped district heating network given a number of potential new consumers. To this end, we state a stationary and nonlinear model of all hydraulic and thermal effects in the pipeline network as well as nonlinear models for consumers and the network’s depot. For the former, we consider the Euler momentum and the thermal energy equation. The thermal aspects are especially challenging. Here, we develop a novel polynomial approximation that we use in the optimization model. The expansion decisions are modeled by binary variables for which we derive additional valid inequalities that greatly help to solve the highly challenging problem. Finally, we present a case study in which we identify three major aspects that strongly influence investment decisions: the estimated average power demand of potentially new consumers, the distance between the existing network and the new consumers, and thermal losses in the network.

scholarly journals Project Portfolio Selection and Scheduling with Resource Allocation, Synergies, and Project Divisibility

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Nancy M. Arratia-Martinez ◽  
Nelly M. Hernandez-Gonzalez ◽  
Fernando Lopez-Irarragorri
Keyword(s):  
Resource Allocation ◽  
Portfolio Selection ◽  
Computing Time ◽  
Decision Problems ◽  
Mixed Integer ◽  
Project Portfolio ◽  
Nonrenewable Resource ◽  
Project Portfolio Selection ◽  
Funding Policies ◽  
Task Level

A project portfolio can be defined as a set of project proposals that are selected according to one or more criteria by a decision-maker (individual or group). Regularly, the portfolio selection involves different decision problems, among those evaluation, selection, scheduling, and resource allocation. In published scientific literature, these problems have been addressed mainly separately giving as a result suboptimal solutions (portfolios). In addition, elements as partial allocation and project representation through tasks constitute relevant characteristics in practice that remain unaddressed in depth. The proposal of this research is to integrate the project selection and project scheduling, incorporating all relevant elements of both decision problems through the scheduling of tasks allowing to determine when the task will be funded and executed. The main impact of precedence rules at the task level in the portfolio is also studied. In this work, Project Portfolio Selection and Scheduling Problem (PPSS) is studied and solved through a new mixed-integer linear programming (MILP) model. The model incorporates renewable and nonrenewable resource allocation, along with partial and total funding policies, project divisibility, and interdependences. Scheduling is integrated into the model, both at the project level and at the project task level, which allows scheduling in noncontiguous periods. Small instances (up to 64 projects) and medium instances (up to 128 projects) were solved optimally in very short times. The relationship between the quality of near-optimal solutions and the solution computing time by modifying the parameters of the solver employed was researched. No significant change in the solution’s quality was perceived, but a significant reduction in solution computing time was achieved. Furthermore, the main effects of precedence rules on solution times and portfolio impact were studied. Results show that even if few precedence rules were introduced, the resource allocation of tasks changed significantly, even though the portfolio impact or the number of projects of the selected portfolios remains the same.

A mixed integer nonlinear optimization model for gas sale company

2006 ◽  
Vol 1 (1) ◽  
pp. 61-69 ◽  
Author(s):  
E. Allevi ◽  
M. I. Bertocchi ◽  
M. T. Vespucci ◽  
M. Innorta
Keyword(s):  
Nonlinear Optimization ◽  
Optimization Model ◽  
Mixed Integer ◽  
Mixed Integer Nonlinear Optimization

A scenario-based mathematical approach to a robust project portfolio selection problem under fuzzy uncertainty

2021 ◽  
pp. 1-14
Author(s):  
Saeed Karimi ◽  
Saeed Mirzamohammadi ◽  
MirSaman Pishvaee
Keyword(s):  
Portfolio Selection ◽  
Confidence Level ◽  
Optimization Model ◽  
Selection Problem ◽  
Programming Approach ◽  
Project Portfolio ◽  
Portfolio Selection Problem ◽  
Project Portfolio Selection ◽  
Proposed Model ◽  
Uncertainty Of Parameters

As a major concern of chief managers in each organization, project portfolio selection has a special place in their responsibilities. To assist managers in making decisions, applicable optimization models play an essential role in such processes. In this regard, this paper provides a stochastic optimization model for a project portfolio selection problem under different scenarios. Providing the novelty in the model along with making it closer to reality, the interdependency between revenue and cost of projects is considered. Due to the inherent uncertainty of parameters, the revenue and cost of each project, as well as contributed capital, follow triangular fuzzy parameters. Contrary to the previous model, the appreciation of assets is considered in the proposed model as the other novelty of the proposed model. To tackle the uncertainty of parameters, a robust possibilistic approach is used, which has been first-ever devised in such problems. Being both optimistic and pessimistic approaches available for decision-makers, a new measure is introduced to make the model inclusive. Moreover, by considering the confidence level as both parameter and decision variables, the robust possibilistic programming approach is adopted to solve the proposed model. Using the new proposed measure, the optimal average value of robust model are obtained under different confidence level. Finally, solving the optimization model, the results are provided by implementing the realization for uncertain parameters, and regarding the obtained results, discussions are made to provide some insights to the managers.

scholarly journals A Hybrid Multi-Population Approach to the Project Portfolio Selection and Scheduling Problem for Future Force Design

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Kyle Robert Harrison ◽  
Saber Elsayed ◽  
Ivan L. Garanovich ◽  
Terence Weir ◽  
Michael Galister ◽  
...  
Keyword(s):  
Portfolio Selection ◽  
Project Portfolio ◽  
Scheduling Problem ◽  
Population Approach ◽  
Project Portfolio Selection
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