&lt;p style='text-indent:20px;'&gt;Sustainable development requires scheduling and implementation of projects by considering cost, environment, energy, and quality factors. Using a robust approach, this study investigates the time-cost-quality-energy-environment problem in executing projects and practically indicates its implementation capability in the form of a case study of a bridge construction project in Tehran, Iran. This study aims to take into account the sustainability pillars in scheduling projects and uncertainties in modeling them. To model the study problem, robust nonlinear programming (NLP) involving the objectives of cost, quality, energy, and pollution level is applied with resource-constrained. According to the results, as time diminished, the cost, energy, and pollution initially decreased and then increased, witha reduction in quality. To make the model close to the real world by considering uncertainties, the cost and quality tangibly improved, and pollution and energy consumption declined. We applied the augmented &lt;inline-formula&gt;&lt;tex-math id="M1"&gt;\begin{document}$ \varepsilon $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;-constraint method to solve the proposed model. According to the result of the research, with regard to the time-cost, time-quality, time-energy, and time-pollution charts, as uncertainty increases, the cost and quality will improve, and pollution and energy will decrease.&lt;/p&gt;&lt;p style='text-indent:20px;'&gt;The proposed model can be employed for all industrial projects, including roads, construction, and manufacturing.&lt;/p&gt; 

A robust time-cost-quality-energy-environment trade-off with resource-constrained in project management: A case study for a bridge construction project

Investigating associations among performance criteria in Green Building projects

This paper presents an overview of the most current topics of interest related to the field of housing and residential building construction. It addresses issues related to industry-wide residential construction trends, policies, innovative technology adoption, construction management, sustainability, energy efficiency, building science, and the need for education, especially regarding architectural concerns. The authors discuss several key technical aspects of residential building, such as structural concerns, building enclosures, and indoor environmental quality issues. Emphasis is placed on the need for renewed research and development efforts, outside-the-box thinking related to financial and investment structures for housing, improved models for adopting innovative technologies in residential construction, new construction management approaches, incorporation of more advanced building science in conjunction with advanced engineered features and architectural design, embracing green and sustai...

Residential Building Construction: State-of-the-Art Review

/pdf/fuzzy-optimization-in-cost-time-and-quality-trade-off-in-xdtsvlv8jk.pdf

Fuzzy Optimization in Cost, Time and Quality Trade-off in Software Projects with Quality Obtained by Fuzzy Rule Base

Particle swarm optimization (PSO), a metaheuristic search algorithm inspired by flocks of birds and schools of fish, has been highly successful in solving a wide range of difficult optimization problems. There has been an exponential growth in the number of publications reporting on the applications of PSO in diverse scientific fields including signal processing, graphics, robotics, and so on. As an optimization tool, PSO has seen similar success in the civil engineering arena, where it has been used in solving shape and size optimization problems in structural design, structural condition assessment and health monitoring, structural material characterization and modeling, transportation network design, traffic flow forecasting, traffic control, traffic accident forecasting, river stage prediction, design optimization of water/wastewater distribution networks, solving reservoir operation problems, parameter estimation/calibration of hydrological models, construction planning, scheduling and management, construction litigation, construction cost estimation and prediction, inverse parameter identification and geotechnical model calibration, slope stability analysis, pavement engineering, and so on. This chapter presents a state-of-the-art review of PSO applications in civil infrastructure systems reported mainly in archival journals and conference proceedings from 1995 (the year of PSO’s inception) until now.

3 – Particle Swarm Optimization in Civil Infrastructure Systems: State-of-the-Art Review

Comprehensive trade-off control on construction time, cost and quality is main aspect of construction project management, and it is significant for improving the benefits of construction projects. This paper presents mathematical models for time, cost and quality separately, and a multi-objective optimization model for time-cost-quality trade-off optimization is set up by synthesizing weighted single-objective models. In a case study, comparing to standard particle swarm optimization (SPSO) and differential evolution algorithm (DE), the most satisfied decision results can be obtained by applying the hierarchical subpopulation particle swarm optimization algorithm (HSPSO) proposed in this paper to solve time-cost-quality trade-off problems. Finally, exhaustive enumeration is given to verify the effectiveness of the models and the feasibility of solution method.

Multi-Objective Optimization in Construction Project Based on a Hierarchical Subpopulation Particle Swarm Optimization Algorithm

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Multi-Objective Optimization in Construction Project Based on a Hierarchical Subpopulation Particle Swarm Optimization Algorithm