Pham, V H S; Nguyen Dang, N T and Nam, N V (2025) Optimizing time and cost in construction projects with a hybridized multi-verse optimizer and opposition-based learning. Engineering, Construction and Architectural Management, 32(7), pp. 4852-4886. ISSN 0969-9988
Abstract
Purpose: For successful management of construction projects, a precise analysis of the balance between time and cost is imperative to attain the most effective results. The aim of this study is to present an innovative approach tailored to tackle the challenges posed by time-cost trade-off (TCTO) problems. This objective is achieved through the integration of the multi-verse optimizer (MVO) with opposition-based learning (OBL), thereby introducing a groundbreaking methodology in the field. Design/methodology/approach: The paper aims to develop a new hybrid meta-heuristic algorithm. This is achieved by integrating the MVO with OBL, thereby forming the iMVO algorithm. The integration enhances the optimization capabilities of the algorithm, notably in terms of exploration and exploitation. Consequently, this results in expedited convergence and yields more accurate solutions. The efficacy of the iMVO algorithm will be evaluated through its application to four different TCTO problems. These problems vary in scale – small, medium and large – and include real-life case studies that possess complex relationships. Findings: The efficacy of the proposed methodology is evaluated by examining TCTO problems, encompassing 18, 29, 69 and 290 activities, respectively. Results indicate that the iMVO provides competitive solutions for TCTO problems in construction projects. It is observed that the algorithm surpasses previous algorithms in terms of both mean deviation percentage (MD) and average running time (ART). Originality/value: This research represents a significant advancement in the field of meta-heuristic algorithms, particularly in their application to managing TCTO in construction projects. It is noteworthy for being among the few studies that integrate the MVO with OBL for the management of TCTO in construction projects characterized by complex relationships.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | evolutionary algorithm; multi-verse optimizer; opposition-based learning; project management; time-cost trade-off |
| Index terms: | exploitation, deviation, evolutionary algorithm, case study, heuristic, time-cost trade-off, project management, methodology, exploration, integration, construction project |
| Subjects: | financial and cost management, risk assessment, data collection methods, organizational analysis, project management theory and practice, quantity surveying, management, environmental resource management, production management, research methods, algorithms |
| Topics: | Organizational Design, Digital Applications, Research Practice, Business Strategy, Cost Management, Sustainability, Risk Management, Project Management |
| Descriptive scope: | 4 PCTE |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here