Variance minimization in resource leveling for self-financing project portfolios: a convex MIQCP approach

Document Type : Research Article

Authors

1 Department of Civil Engineering, Ne.C., Islamic Azad University, Neyshabur, Iran.

2 Department of Civil Engineering, Hakim Sabzevari University, Sabzevar, Iran

3 Department of Mathematics, Ne.C., Islamic Azad University, Neyshabur, Iran

4 Department of Civil Engineering, Ne.C., Islamic Azad University, Neyshabur, Iran

Abstract

This study addresses the critical trade-off between financial returns and operational stability  in capital-intensive project portfolios. We propose a novel convex Mixed-Integer Quadratically Constrained Programming (MIQCP) framework that unifies Net Present Value (NPV) maximization, strict self-financing, and direct resource variance minimization. Unlike existing non-convex or heuristic models, our approach endogenizes flexible phasing strategies and introduces a dual-buffer mechanism to protect both liquidity and resource capacity. By exploiting the positive semi-definite properties of the quadratic constraints, we ensure global optimality for portfolios with 50+ activities. Computational results reveal a significant ”constrainedness” effect, where tighter financial and precedence constraints accelerate convergence by pruning the search tree. Findings demonstrate that a negligible NPV sacrifice (< 2%) yields disproportionate gains in resource stability (> 8%), providing a high-fidelity decision-support tool for managing internal capital markets under high volatility.

Keywords

Main Subjects

References

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Journal of Mathematical Modeling
Volume 14, Issue 3
August 2026
Pages 1005-1025

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