Optimization Model Calculation of Construction Cost and Time Based on Genetic Algorithm

He, Wei; Shi, Yichao; Kong, Dewei

doi:10.1088/1755-1315/242/6/062044

Cited by 4 publications

(1 citation statement)

References 7 publications

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“…Hence, they are utilized as a search and planning tool for project scheduling problems that are NP-hard problems [19,41]. GAs can provide good enough and fast enough solutions without mathematical rigor, and because of that, GAs have been widely utilized for construction project optimization [55][56][57]. Haque and Hasin [58] used a GA as a searching tool to solve the time-cost optimization problem of projects under uncertain conditions and fuzzy time periods.…”

Section: Evolutionary Algorithmsmentioning

confidence: 99%

Systematic Review of the Time-Cost Optimization Models in Construction Management

2023

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The construction sector is a crucial contributor to the national and global economy. Therefore, improving the efficiency and effectiveness of construction projects can have a significant impact on gross domestic product (GDP). However, managing construction projects can be challenging due to the uncertainties and complexities involved. The three primary interrelated constraints of construction projects, namely, time, scope, and cost, require effective management to ensure successful completion. To optimize the time and cost of construction projects, various optimization models and techniques have been proposed in the literature. This paper presents a systematic review of the time-cost optimization models in construction management and proposes some future work to improve the solution of the considered problem. The review categorizes the existing models into three categories: exact models, approximate models, and hybrid algorithm models. The exact models provide optimal solutions but require a lot of computational time and may not be efficient in solving multi-objective and large-scale problems. The approximate models provide near-optimal solutions and reduce computational effort but may not be efficient in solving large-scale projects. The hybrid algorithm models combine the good properties of different algorithms to provide high-quality and efficient solutions. The purpose of this paper is accomplished through a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The paper analyzes the contribution, advantages, and limitations of each category and provides recommendations for future work. Based on the review, several recommendations for future work are provided, including the development of hybrid models that combine different optimization techniques, the incorporation of risk management into optimization models, and the use of advanced data analytics techniques to improve the accuracy of optimization models. Overall, this paper provides an up-to-date comprehensive review of the time-cost optimization models used in construction management and offers valuable insights for researchers and practitioners in this field. The findings of this review can be used to guide future research and improve the effectiveness of optimization models for construction projects.

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Section: Evolutionary Algorithmsmentioning

confidence: 99%

Systematic Review of the Time-Cost Optimization Models in Construction Management

2023

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Balanced Optimization System of Construction Project Management Based on Improved Particle Swarm Algorithm

Wang¹

2021

Lecture Notes on Data Engineering and Communications Technologies

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Time and finance optimization model for multiple construction projects using genetic algorithm

Hasan

Mohammed

2022

Journal of the Mechanical Behavior of Materials

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Construction contractors usually undertake multiple construction projects simultaneously. Such a situation involves sharing different types of resources, including monetary, equipment, and manpower, which may become a major challenge in many cases. In this study, the financial aspects of working on multiple projects at a time are addressed and investigated. The study considers dealing with financial shortages by proposing a multi-project scheduling optimization model for profit maximization, while minimizing the total project duration. Optimization genetic algorithm and finance-based scheduling are used to produce feasible schedules that balance the finance of activities at any time with the available funds. The model has been tested in multi scenarios, and the results are analyzed. The results show that negative cash flow is minimized from −693,784 to −634,514 in enterprise I and from −2,646,408 to −2,529,324 in enterprise II in the first scenario and also results show that negative cash flow is minimized to −612,768 with a profit of +200,116 in enterprise I and to −2,597,290 with a profit of +1,537,632 in enterprise II in the second scenario.

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Optimization Model Calculation of Construction Cost and Time Based on Genetic Algorithm

Cited by 4 publications

References 7 publications

Systematic Review of the Time-Cost Optimization Models in Construction Management

Systematic Review of the Time-Cost Optimization Models in Construction Management

Balanced Optimization System of Construction Project Management Based on Improved Particle Swarm Algorithm

Time and finance optimization model for multiple construction projects using genetic algorithm

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