Particle Swarm Optimization in Managing Construction Problems

Sahib, Naji Mutar; Hussein, Abtehaj

doi:10.1016/j.procs.2019.06.039

Cited by 8 publications

(4 citation statements)

References 5 publications

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“…The optimisation method adopted by the RRM platform is based on the bio-inspired Particle Swarm Optimisation (PSO) algorithm (Sahib & Hussein, 2019). This algorithm integrates very few hyperparameters to search and identify an optimal solution while only the objective function is required, which makes it easy to implement and use.…”

Section: Optimisation and Planning Componentsmentioning

confidence: 99%

A distributed collaborative platform for multi-stakeholder multi-level management of renovation projects

Doukari,

Kassem,

Greenwood

2024

ITcon

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To meet European energy-saving and decarbonisation goals, the annual renovation rate of buildings requires to be at least twice its current level; an aspiration to which the use of innovative and automated solutions can contribute. This paper presents such a solution, the RINNO Retrofitting Manager (RRM) which is part of a large, ambitious research and development project (RINNO) that aims to provide an augmented intelligence-enabled framework for deep, energy-focused retrofitting of buildings. The RRM uses web-service technologies to rationalise the retrofitting process and optimise the delivery of renovation works, while making data readily accessible through an integrated set of role-based user interfaces. The RRM is designed and developed as an open distributed system, that is extensible and portable, by implementing a collaborative research and development approach. The RRM platform implements a multi-level, multi-stakeholder planning approach. It addresses the dearth, insufficiency, and isolation of existing renovation tools by enhancing collaboration, interoperability, and data security, and avoiding information loss and misunderstanding. Employing the Unified Theory of Acceptance and Use of Technology (UTAUT) model, tests conducted with users from independent construction organisations confirmed the RRM's satisfactory performance, ease of deployment, and overall suitability for the management of renovation projects. While this research provides a free collaborative platform for managing renovation projects that can be used by all building retrofit stakeholders in Europe, it also introduces a set of web-services that can be easily reused by third-party developers and integrated into their software tools.

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Section: Optimisation and Planning Componentsmentioning

confidence: 99%

A distributed collaborative platform for multi-stakeholder multi-level management of renovation projects

Doukari,

Kassem,

Greenwood

2024

ITcon

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“…Thus, PSO follows the same behavior to optimize the problem by iteratively improving a population of possible solutions, called particles, with respect to a given degree of quality [75]. The problem is solved by moving these particles in the search space based on a mathematical formula of the particles' positions and velocities [76,77]. The movement of each particle is influenced by its local best-known position, but it is also guided toward the best recognized positions in the search space.…”

Section: Swarm Intelligence (Si) Algorithmsmentioning

confidence: 99%

“…The movement of each particle is influenced by its local best-known position, but it is also guided toward the best recognized positions in the search space. Then, these positions are updated to better positions found by other particles [76,77]. Several researchers have utilized PSO to solve TCT problems [78][79][80].…”

Section: Swarm Intelligence (Si) 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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“…Particle swarm optimization (PSO) has proven to be a powerful method for optimization problems [17]. Adopting PSO, Poitras et al [18] investigated the optimum floor configuration by minimizing the total mass or cost while satisfying all design criteria.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Wind Turbine Towers Optimization with a Parallel Updated Particle Swarm Algorithm

Chen

et al. 2021

Applied Sciences

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The prestressed concrete–steel hybrid (PCSH) wind turbine tower, characterized by replacing the lower part of the traditional full-height steel tube wind turbine tower with a prestressed concrete (PC) segment, provides a potential alterative solution to transport difficulties and risks associated with traditional steel towers in mountainous areas. This paper proposes an optimization approach with a parallel updated particle swarm optimization (PUPSO) algorithm which aims at minimizing the objective function of the levelized cost of energy (LCOE) of the PCSH wind turbine towers in a life cycle perspective which represents the direct investments, labor costs, machinery costs, and the maintenance costs. Based on the constraints required by relevant specifications and industry standards, the geometry of a PCSH wind turbine tower for a 2 MW wind turbine is optimized using the proposed approach. The dimensions of the PCSH wind turbine tower are treated as optimization variables in the PUPSO algorithm. Results show that the optimized PCSH wind turbine tower can be an economic alternative for wind farms with lower LCOE requirements. In addition, compared with the traditional particle swarm optimization (PSO) algorithm and UPSO algorithm, the proposed PUPSO algorithm can enhance the optimization computation efficiency by about 60–110%.

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Particle Swarm Optimization in Managing Construction Problems

Cited by 8 publications

References 5 publications

A distributed collaborative platform for multi-stakeholder multi-level management of renovation projects

A distributed collaborative platform for multi-stakeholder multi-level management of renovation projects

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

Hybrid Wind Turbine Towers Optimization with a Parallel Updated Particle Swarm Algorithm

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