Integration of resource supply management and scheduling of construction projects using multi-objective whale optimization algorithm and NSGA-II

Ghoroqi, Mahyar and Ghoddousi, Parviz and Makui, Ahmad and Shirzadi Javid, Ali Akbar and Talebi, Saeed (2024) Integration of resource supply management and scheduling of construction projects using multi-objective whale optimization algorithm and NSGA-II. Soft Computing. ISSN 1432-7643

Text Final Draft - Ghoroqi - SOCO-D-22-01231_R1-20231114-Accept.pdf - Accepted Version Restricted to Repository staff only until 19 January 2025. Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB)

Abstract

This study explores the intricate integration and synchronization of supplier selection with the optimal scheduling of multi-mode resource-constrained projects, which is a genuine and complex challenge prevalent in the construction industry, by proposing new multi-objective mathematical modeling considering various items. Within this context, a multifaceted network of concurrent projects (multiproject) is examined with different suppliers' resources (multi-supplier) to minimize the overall projects' delay times and associated costs. The mathematical model formulation also incorporates diverse implementation modes (multi-mode) and the time value of money (TVM). In order to use and unravel the complexities of the proposed model, two distinct algorithms, including a multi-objective whale optimization algorithm (WOA) based on the Pareto archive and the well-known non-dominated sorting genetic algorithm II (NSGA-II), are employed. The algorithms were subjected to a comparative analysis of several sample problems and evaluated against multi-objective criteria, including quality metric (QM), diversity metric (DM), spacing metric (SM), number of solutions (NOS), mean Ideal distance (MID), and computational time. The evaluation reveals that the tailored multi-objective WOA outperforms NSGA-II, exhibiting greater solution precision and diversity. The WOA demonstrates an enhanced ability to efficiently explore the problem's feasible solution space, albeit at the increased computational time to pinpoint optimal solutions. Notably, the validity and practicality of the proposed model and method were field-tested within the context of construction projects in Iran, with the obtained results juxtaposed against the real-world data. The comparative analysis indicates that implementing the scheduling approach and solution methodology espoused by the multi-objective WOA led to significant improvements, with financial gains of up to 6% and time savings reaching 16%. Overall, this research substantiates the proposed model and algorithms' benefits in reducing project costs and delays, offering valuable insights for construction industry practitioners.

Item Type:	Article
Identification Number:	https://doi.org/10.1007/s00500-023-09467-0
Dates:	Date Event 13 November 2023 Accepted 19 January 2024 Published Online
Uncontrolled Keywords:	Multi-project scheduling, Supply management, Mathematical modeling, Optimization algorithms, Construction industry
Subjects:	CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-01 - engineering (non-specific) CAH13 - architecture, building and planning > CAH13-01 - architecture, building and planning > CAH13-01-02 - building
Divisions:	Faculty of Computing, Engineering and the Built Environment > School of Engineering and the Built Environment > Dept. of Built Environment
Depositing User:	Gemma Tonks
Date Deposited:	20 Nov 2023 15:09
Last Modified:	19 Feb 2024 16:13
URI:	https://www.open-access.bcu.ac.uk/id/eprint/14958

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