A Review on Fuzzy - AHP technique in Environmental Impact Assessment of Construction Projects, India

There are several countries today using procedures for Environmental impact assessment (EIA) is based on a series of mathematical techniques which attempt to localize, describe and assess the positive and negative effects that any human activity has on our environment, generally causing it to deteriorate. The environmental impact assessment (EIA) of projects requires the evaluation of the effects of very diverse actions on a number of different environmental factors, the uncertainty and inaccuracy being inherent in the process of allocating values to environmental impacts carried out by a panel of experts, stakeholders and affected population. The application of the fuzzy Logic and AHP technique can be helpful in identification of the risk associated with construction or developing project and improves the study of EIA. Fuzzy is one of the characteristics of human thoughts for which fuzzy sets theory is an effective tool for fuzziness. A fuzzy logic knowledge-based approach can be used for the environmental impact assessment study of the different construction projects. The review article highlights the role of Fuzzy AHP logic method in EIA of different construction projects, fuzzy logic modeling - software for fuzzy EIA, fuzzy numbers and steps of fuzzy methods as well as reveals that how fuzziness can be determined by applying fuzzy logic method in construction projects

Decision Support Model For Construction Crew Reassignments

The reassignment of crews on a construction project in response to changes occurs on a frequent basis. The factors that affect the crew reassignment decision can be myriad and most are not known with certainty. This research addresses the need for a decision support model to assist construction managers with the crew reassignment problem. The model design makes use of certainty factors in a decision tree structure. The research helped to determine the elements in the decision tree, the appropriate combination rules to use with the certainty factors, and the method for combining the certainty factors and costs to develop a measure of cost for each decision option. The research employed surveys, group meetings, and individual interviews of experienced construction managers and superintendents to investigate the current methods used by decision makers to identify and evaluate the key elements of the construction crew reassignment decision. The initial research indicated that the use of certainty factors was preferred over probabilities for representing the uncertainties. Since certainty factors have not been used in a traditional decision tree context, a contribution of the research is the development and testing of techniques for combining certainty factors, durations, and costs in order to represent the uncertainty and to emulate the decision process of the experts interviewed. The developed model provides the decision maker with an estimate of upper and lower bounds of costs for each crew reassignment option. The model was applied contemporaneously to six changes on three ongoing construction projects to test the model and assess its usefulness. The model provides a previously unavailable tool for the prospective identification and estimation of productivity losses and potential costs that emanate from changes. The users indicated the model process resulted in concise and complete compilations of the elements of the crew reassignment decision and that the model outputs were consistent with the users\u27 expectations

Determining Interconnectedness of Barriers to Interface Management in Large Construction Projects

This study aims to identify the crucial barriers to interface management and understand the interdependencies in Large Infrastructure Construction Projects (LICP). Three-pronged sequential explanatory mixed methods research is adopted comprising a structured survey of experts (n=102) and semi-structured interviews (n=13). Subsequently, interpretive structural modelling (ISM) integrated with fuzzy protocol is used to analyse pairwise interrelationships among these factors. A ‘Multi-layered IM barrier’ model is developed with ‘Process related issues,’ 'Misaligned incentives among project stakeholders' and 'Frequent Change Orders' as the manifested barriers. On the other hand, this study also prioritized the barriers and classified them as driving, linking, and independent. The outcome of this study presents the interdependence of barriers and classification of barriers, focusing on proactive action on driving barriers, which is crucial to the knowledge of interface management. The impact position of LICP with the identified project issues can be compared against ‘Multi-layered IM barriers’ and can help project teams better strategize IM by focusing on essential barriers. In addition, such exercises can improve the coordination among participants in construction projects. Using a structured approach to identifying interdependencies among barriers to IM is a significant original contribution by the study

Risk management in fast-track projects

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.This thesis is about risk management in fast-track construction projects. The aim of the study is to identify the risks in the UAE construction industry, understand how they are dealt with, and propose more effective frameworks for risk management in fast-track construction. A mixed method approach was used to fulfil the objectives of the study. 65 questionnaires were distributed to professionals in the construction industry, including contractors, sub-contractors, project managers and private consultants. Their responses were analysed using statistical techniques, and the results taken for discussion to a focus group of eleven experienced construction managers and experts. Secondary data was also collected via literature reviews of print and website articles, and of books and documents from company, government and industry-specific databases. The findings show that risks in construction projects can be internal or external, and that in the UAE, owner- and design-related risks are seen as the most significant. Knowledge about risk management is present, but more needs to be done to eradicate the problems associated with poorly managed fast-track construction projects. Using the suggestion of the focus group, a framework for risk mitigation was developed based on the Alien Eyes’ risk and Qualitative Risk Management models. The study discusses the implications of risk management for practitioners and academicians in the construction industry. Poor risk management, which is usually the consequence of inadequate recognition of and/or responsiveness to risks and uncertainties, can have a devastating impact upon projects. It is hoped that practitioners applying the findings and suggestions in this study will see positive change, improved profitability and greater competitive advantage as a result.Abu Dhabi Polic

Ranking Risks of BOT Toll Road Investment Projects in Indonesia Using Fuzzy Interpretive Structural Modelling

The Government of Indonesia implemented the Build, Operate, and Transfer (BOT) model, relying on private investment to bridge the financing gap in developing public infrastructure facilities, including toll roads. Toll road investments, like other greenfield infrastructure projects, are typically characterized by high project risk, which discourages private sector investment. Many previous studies have investigated the various risk events in toll road investment projects, but only a few have assessed the interrelationships of risk events in the Indonesian context. This study fills this knowledge gap by determining which risk event influences other events most. Fuzzy interpretive structural modelling combined with the matrix impact of cross-references multiplication applied to a classification method was used to determine the hierarchy of risk events and analyze their influences on other risk events. A total of fourteen risk events were identified and analyzed. An unclear output specification was found to be the most significant risk event, with the biggest driving power affecting other risks. The findings and limitations of this study point the way forward for future research

Developing a fuzzy-based model to assess and allocate risks in Syrian construction projects

Construction industry has always been a place of growing interest. It is mostly known, however, for its poor reputation for managing risks that inevitably come across a great number of the activities it involves. Those risks are simply described as a disruption for what is a rather normal task. Some of those risks can be impactful in a way that cannot be foreseen and would be catastrophic for the client and for the contractor. Assessing and allocating risks in a construction project is then a key component of an integrated, efficient, and successful risk management of every construction project. It is, however, shrouded with ambiguity, uncertainty, human judgment, and natural expressions. This makes fuzzy-based approaches more suitable to make a final assessment. This paper aims to develop a fuzzy-based model to predict major risks liability and magnitude based on a series of questionnaire with experienced engineers in Lattakia, Syria. This prototype model is developed using Matlab and fuzzy-set theory to make more reliable decisions and to avoid costly overruns especially in the early phases of the project where few or no information is available

Deterministic and Probabilistic Risk Management Approaches in Construction Projects: A Systematic Literature Review and Comparative Analysis

Risks and uncertainties are inevitable in construction projects and can drastically change the expected outcome, negatively impacting the project’s success. However, risk management (RM) is still conducted in a manual, largely ineffective, and experience-based fashion, hindering automation and knowledge transfer in projects. The construction industry is benefitting from the recent Industry 4.0 revolution and the advancements in data science branches, such as artificial intelligence (AI), for the digitalization and optimization of processes. Data-driven methods, e.g., AI and machine learning algorithms, Bayesian inference, and fuzzy logic, are being widely explored as possible solutions to RM domain shortcomings. These methods use deterministic or probabilistic risk reasoning approaches, the first of which proposes a fixed predicted value, and the latter embraces the notion of uncertainty, causal dependencies, and inferences between variables affecting projects’ risk in the predicted value. This research used a systematic literature review method with the objective of investigating and comparatively analyzing the main deterministic and probabilistic methods applied to construction RM in respect of scope, primary applications, advantages, disadvantages, limitations, and proven accuracy. The findings established recommendations for optimum AI-based frameworks for different management levels—enterprise, project, and operational—for large or small data sets

An analytic network process model to prioritize supply chain risks in green residential megaprojects

Megaprojects and specifically ‘green’ construction of residential megaprojects can contain significant risks of failure. To design proper risk mitigation strategies, after identifying key risk factors, the next step is to conduct assessments that would facilitate the process of risk element prioritization. Risk assessment comprises the establishment of factor interrelation and discerning the indicators of importance. This research proposes a novel version of an integrated prioritization method and analyzes twelve all-inclusive key supply chain oriented risk factors identified in a previous study. Through a comprehensive literature review three criteria, impact, probability, and manageability are selected. Also, a fourth criterion namely influence rate is included in the model, based on the driving powers that can also be derived from the Interpretive Structural Modeling’s (ISM) assessment. Fundamentally, the calculations hinge on the Analytic Network Process (ANP) method which provides an assessment of the alternatives’ weights based on pairwise comparisons concerning the criteria specified. To enhance the accuracy of the perceptive judgments of the expert panelists, a bell-shaped fuzzy function is used to convert the verbal statements to crisp values. In addition, Row Sensitivity Analysis is administered to check the stability of the results and provide predictive scenarios. To validate the model, a case study, located in Iran, was conducted, where an expert panel consisting of four individuals made the pair-wise comparisons through an ANP questionnaire. Results indicate priority and sensitivity of the alternatives concerning criteria, for the case under study

Role of Evolutionary Algorithms in Construction Projects Scheduling

Due to the increase in the stakeholders and their objectives the construction projects have significantly been affected by the ongoing demands leading to increase in complexity of scheduling problems, research in the field of Multi-Objective Optimization (MOO) have increased significantly. Through their population-based search methodologies, Evolutionary Algorithms drove attention to their efficiency in addressing scheduling problems involving two or three objectives. Genetic Algorithms (GA) particularly have been used in most of the construction optimization problems due to their ability to provide near-optimal Pareto solutions in a reasonable amount of time for almost all objectives. However, when optimizing more than three objectives, the efficiency of such algorithms degrades and trade-offs among conflicting objectives must be made to obtain an optimal Pareto Frontier. To address that, this paper aims to provide a comparative analysis on four evolutionary algorithms (Genetic algorithms – Memetic algorithms – Particle Swarm – Ant colony) in the field of construction scheduling optimization, gaps are addressed, and recommendations are proposed for future research development