Fuzzy modeling of allocation of financial resources of sustainable projects and Solving with GSSA algorithm
Subject Areas : Artificial Intelligence
Mohsen
Amini Khouzani
1
(Department of Financial Engineering, Shahr-e-Qods Branch, Islamic Azad University,Tehran, Iran)
Alireza
Sadeghi
2
(Department of Financial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran)
Amir
Daneshvar
3
(Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran)
Adel
Pourghader Chobar
4
(Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran)
Keywords: Resource allocation, Meta-Heuristic Algorithms, Fuzzy programming, sustainable projects,
Abstract :
The problem of allocation of financial resources in projects is one of the most important problems of mathematical optimization. Incorrect allocation of financial resources can lead to project failure, increased costs, and reduced profitability. The importance of this issue has led to the modeling of a financial resource allocation problem for sustainable projects under uncertainty in this article. A fuzzy programming method was used to control model parameters and GSSA, GA, and SSA algorithms were used to solve the model. In the mathematical model, the goal was to optimize the objective function consisting of predicted return, investment risk, and project sustainability. Mathematical calculation results showed that meta-heuristic algorithms have high efficiency in achieving optimal solutions in a short time. so that the average time to solve them was less than 10 seconds. Also, the calculation results showed that increasing the uncertainty rate leads to increasing the value of the objective function and creating a distance from the optimal point. This is due to increasing costs and decreasing profits in sustainable projects. Finally, usage the TOPSIS method, the ranking of solving algorithms was done, and the GSSA algorithm was the most efficient algorithm among other algorithms with a desirability weight of 0.846.