طراحی ساختار برنامه‌ریزی ریاضی چندهدفه (MOLP) برای ارزیابی و بهبود کارایی ارزشی در مدیریت پروژه‌های عمرانی

علی   صداقت پور; مرتضی شفیعی; محمد رضا مظفری; حسن سلطانی

Authors

Ali Sedaghatpour Department of Industrial Management, KI.C., Islamic Azad University, Kish, Iran Author https://orcid.org/0009-0006-1447-7952
Morteza Shafiee Department of Industrial Management, KI.C., Islamic Azad University, Kish, Iran Translator https://orcid.org/0000-0003-2926-4168
Mohammad Reza Mozaffari Department of Mathematics, Shi.C., Islamic Azad University, Shiraz, Iran Author https://orcid.org/0009-0001-7839-7146
Hassan Soltani Department of Industrial Management, Shi.C., Islamic Azad University, Shiraz, Iran Author https://orcid.org/0000-0002-2192-9738

Keywords:

Multi, objective optimization, data envelopment analysis, directed distance function, value efficiency, construction projects

Abstract

Objective: This study aimed to design and propose a multi-objective mathematical programming structure for assessing and improving the value efficiency of civil projects by integrating Data Envelopment Analysis with managerial preference information.

Methodology: This applied quantitative study employed a mathematical modeling approach. The study population consisted of civil projects implemented by the Sadra New City Development Company, and all 33 available projects were included as decision-making units through a census approach. Contract amount, contract duration, contract extension duration, and net contractor receivables were specified as model inputs, while physical progress and project quality percentages were considered outputs. Project value efficiency was assessed using Data Envelopment Analysis based on the directional distance function under three technological regimes: constant returns to scale (CRS), variable returns to scale (VRS), and Free Disposal Hull (FDH). Managerial preference information was incorporated into the evaluation framework through multi-objective linear programming. Efficiency was additionally examined using input-oriented, output-oriented, and combined directional specifications.

Findings: Under the CRS technology, 9 of the 33 projects were identified as fully efficient, with an average efficiency score of 80.64%. Under VRS, the number of efficient projects increased to 24, and the mean efficiency reached 98.27%. The FDH technology identified 26 efficient projects and produced the highest mean efficiency score of 98.56%. Project 3 appeared in the reference set of seven of the nine inefficient VRS projects and was identified as the principal performance benchmark. Nine projects achieved complete efficiency under both CRS and VRS technologies, indicating relatively robust performance across scale assumptions. In contrast, Project 11 ranked lowest overall, with an efficiency score of 85.00% under VRS and 69.79% under CRS.

Conclusion: The proposed framework provides an effective quantitative mechanism for integrating multi-objective programming, Data Envelopment Analysis, and managerial preferences. It facilitates the identification of benchmark projects, distinguishes scale-related from managerial inefficiencies, and provides practical guidance for improving the financial and temporal management of civil projects.

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