में बचाया:
ग्रंथसूची विवरण
मुख्य लेखकों: Mirnezami, Seyed-Ali, Ghasemi, Mohammad, Shahabi-Shahmiri, Reza
स्वरूप: Preprint
प्रकाशित: 2025
विषय:
ऑनलाइन पहुंच:https://arxiv.org/abs/2509.00002
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author Mirnezami, Seyed-Ali
Ghasemi, Mohammad
Shahabi-Shahmiri, Reza
author_facet Mirnezami, Seyed-Ali
Ghasemi, Mohammad
Shahabi-Shahmiri, Reza
contents Owing to the importance of project cash flow, which comprises an entire history of all cash inflows and cash outflows, to economic survival of firms, it is vital to coping with project scheduling issues considering resource constraints in circumstances involving cash flow. Furthermore, since appropriate project management is subject to the innate uncertainties involved in most projects, they are required to be appraised respecting their profound impact. In this paper, a new comprehensive multi-mode multi-objective linear programming model with two conflicting objectives, which are maximizing final cash flow for profit optimization and shortening the duration of project execution, considering improving assumptions, that is, payments delays, project finance constraints, initial capital, different types of interest rates, credit limit to assuage financial distress, credit line usage, is presented in an uncertain environment. Since the model is considered as multi-objective with uncertain parameters, a new extended interval valued fuzzy - Torabi and Hassini (IVF-TH) approach is proposed to tackle the problem. The presented mixed integer linear programming (MILP) model is solved applying CPLEX solver. In addition, a real construction project in oil and gas industry is presented as a case study to illustrate the model applications. Ultimately, for the purpose of assessing the outcomes, a sensitivity analysis is implemented, and the performance of the proposed solution approach is compared to the previous multi-objective optimization methods using both case study and large problem instances.
format Preprint
id arxiv_https___arxiv_org_abs_2509_00002
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A New Bi-Objective Model for Resource-Constrained Project Scheduling and Cash Flow Problems with Financial Constraints under Uncertainty: A Case Study
Mirnezami, Seyed-Ali
Ghasemi, Mohammad
Shahabi-Shahmiri, Reza
General Mathematics
Owing to the importance of project cash flow, which comprises an entire history of all cash inflows and cash outflows, to economic survival of firms, it is vital to coping with project scheduling issues considering resource constraints in circumstances involving cash flow. Furthermore, since appropriate project management is subject to the innate uncertainties involved in most projects, they are required to be appraised respecting their profound impact. In this paper, a new comprehensive multi-mode multi-objective linear programming model with two conflicting objectives, which are maximizing final cash flow for profit optimization and shortening the duration of project execution, considering improving assumptions, that is, payments delays, project finance constraints, initial capital, different types of interest rates, credit limit to assuage financial distress, credit line usage, is presented in an uncertain environment. Since the model is considered as multi-objective with uncertain parameters, a new extended interval valued fuzzy - Torabi and Hassini (IVF-TH) approach is proposed to tackle the problem. The presented mixed integer linear programming (MILP) model is solved applying CPLEX solver. In addition, a real construction project in oil and gas industry is presented as a case study to illustrate the model applications. Ultimately, for the purpose of assessing the outcomes, a sensitivity analysis is implemented, and the performance of the proposed solution approach is compared to the previous multi-objective optimization methods using both case study and large problem instances.
title A New Bi-Objective Model for Resource-Constrained Project Scheduling and Cash Flow Problems with Financial Constraints under Uncertainty: A Case Study
topic General Mathematics
url https://arxiv.org/abs/2509.00002