Purpose: Factors influencing management of construction and demolition (C&D) waste within the Iranian context have yet to be investigated. The purpose of this paper is to define and address this knowledge gap, through development of a model to map the associations among the primary factors affecting C&D waste at project, industry and national levels. Design/methodology/approach: A conceptual model is developed based on synthesising the findings of available studies on factors affecting C&D waste with a focus on developing countries. For collecting data, the study drew upon a questionnaire survey of 103 Iranian construction practitioners. The strength and significance of associations among these factors to modify and validate the model were assessed using the structural equation modelling-partial least squares approach. Findings: Major factors affecting C&D waste management and their level of importance were identified at project, industry and national levels. Results clearly showed that the government should review regulations pertaining to C&D waste management and make sure they are implemented properly. The “polluter pays principle” is a useful guide in devising effective policies and regulations for the Iranian context. Originality/value: This study contributes to the field through presenting the first major study on C&D waste management in Iran. The study provides a picture of C&D waste management status quo in Iran and encapsulates the factors affecting C&D waste management in the Iranian context at different levels within an integrated model. The findings have practical implications for policy makers and construction practitioners in Iran, similar developing economies and foreign firms planning to operate in Iran.

The construction industry includes a large number of specialized areas and disciplines, most of which are based on cyclical processes during the construction phase. With the introduction of the lean construction concept, researchers have begun to apply lean principles to construction processes. The research described in this paper applies lean principles to a construction operation using computer simulation. Simulation makes it possible to evaluate the effects of implementing lean principles into construction processes prior to real world application. A case study of the bricklaying process was conducted to quantify and evaluate the results of applying lean principles. Data required for constructing the simulation model were gathered from the construction site through work and time study techniques. Preliminary results show improvement opportunities exist in the bricklaying process due to a high share of non value-adding work. The results of lean principles implementation also reveal that lean principles can enhance the performance of the bricklaying process through more than 40% productivity improvement.

In this study, the multi-mode resource-constrained multi-project scheduling problems (MMRCMPSPs) considering supply management and sustainable approach in the construction industry under uncertain conditions have been investigated using evidence theory to mathematical modeling and solving by multi-objective optimization algorithms. In this regard, a multi-objective mathematical model has been proposed, in which the first objective function aims to maximize a weighted selection of projects based on economic, environmental, technical, social, organizational, and competitive factors; the second objective function is focused on maximizing profit, and the third objective function is aimed at minimizing the risk of supply management. Moreover, various components, such as interest rates, carbon penalties, and other implementation limitations and additional constraints, have also been considered in the modeling and mathematical relationships to improve the model’s performance and make it more relevant to real-world conditions and related issues, leading to better practical applications. In the mathematical modeling adopted, the processing time of project activities has been considered uncertain, and the evidence theory has been utilized. This method can provide a flexible and rational approach based on evidence and knowledge in the face of uncertainty. In addition, to solve the proposed multi-objective mathematical model, metaheuristic optimization algorithms, such as the differential evolution (DE) algorithm based on the Pareto archive, have been used, and for evaluating the results, the non-dominated sorting genetic algorithm II (NSGA-II) has also been employed. Furthermore, the results have been compared based on multi-objective evaluation criteria, such as quality metric (QM), spacing metric (SM), and diversity metric (DM). It is worth noting that to investigate the performance and application of the proposed model, multiple evaluations have been conducted on sample problems with different dimensions, as well as a case study on residential apartment construction projects by a contracting company. In this respect, the answers obtained from solving the model using the multi-objective DE algorithm were better and superior to the NSGA-II algorithm and had a more favorable performance. Generally, the results indicate that using the integrated multi-objective mathematical model in the present research for managing and scheduling multi-mode resource-constrained multi-project problems, especially in the construction industry, can lead to an optimal state consistent with the desired objectives and can significantly improve the progress and completion of projects.

The construction industry has been criticized as being a non-sustainable industry that requires effective tools to monitor and improve its sustainability performance. The multiplicity of indicators of the three pillars of sustainability—economic, social, and environmental—complicates construction sustainability assessments for project managers. Therefore, prioritizing and selecting appropriate sustainability indicators (SIs) is essential prior to conducting a construction sustainability assessment. The main purpose of this research is to select the most appropriate set of SIs to address all three pillars of highway sustainability by a new group decision-making approach. The proposed approach accounts for risk attitudes of experts and entropy measures under a triangular intuitionistic fuzzy (TIF) environment, to handle the inherent uncertainty and vagueness that is present throughout the evaluation process. Furthermore, new separation measures and ranking scores are introduced to distinguish the preference order of SIs. Eventually, the approach is implemented in a case study of highway construction projects and the applicability of the approach is examined. To investigate the stability and validity of computational results, a sensitivity analysis is carried out and a comparison is made between the obtained ranking outcomes and the traditional decision-making methods.

Sustainable construction has recently been acknowledged as a crucial issue in the construction industry. Developing and using multicriteria evaluation models to prioritize alternative construction projects based on sustainability indicators plays a major role in promoting sustainable construction. Evaluating construction projects according to sustainable development principles is a complicated problem, because the evaluation includes various indicators that have complex interdependences. Moreover, sufficient data is not normally available for the evaluation of construction projects from a sustainability point of view. To overcome these problems, this paper introduces a novel multicriteria group decision-making (MCGDM) model based on bootstrap simulation. The proposed model uses nonparametric bootstrap simulation to address aggregating inadequate experts’ opinions and employs decision-making trial and evaluation laboratory (DEMATEL) and fuzzy cognitive map (FCM) to provide the relative importance of evaluation criteria. Furthermore, based on the positive-ideal, negative-ideal, and closeness coefficient in interval intuitionistic trapezoidal fuzzy sets, a novel ranking score is proposed to compute the sustainability level of the construction projects. The proposed model is employed in a case study for evaluating and prioritizing highway construction projects by considering sustainability indicators. The main contribution of this paper is the development of a novel and applicable mathematical model to assist decision makers (DMs) in evaluating various alternative projects and making the optimum decision based on an integrated consideration of economic, environmental, and social sustainability indicators.