Social Sustainability Indicators in Mass Housing Construction

In the construction industry, buildings constitute more than half of the new construction built in the world. With the rapid growth of population in urban areas and high-energy consumption of buildings, considerable attention and efforts have been devoted to creating a sustainably built environment. As a result, various sustainable rating systems, principles and tools have been developed in recent years. This paper presents efforts underway for evaluation of sustainability in mass housing construction projects in the Middle East from a social aspect. The study reviews reports, guidelines and best practices at national and international levels to detect key sustainability indicators. The paper analyzes and evaluates the social perspective of sustainable rating systems of Envision, LEED, BREEM, CASBEE and Green Globes. The research team fine-tuned and assessed the indicators extracted from these guidelines through surveys and content analysis. Based on the analysis, four major categories are identified as critical indicators in the decision-making and planning of mass housing construction. This set of criteria aim toward creating a more sustainable society, which have better community and construction interactions; improved health, safety, and livability; lower risk; and neighborhood characteristics from a project life cycle standpoint

Finding Optimum Resource Allocation to Optimizing Construction Project Time/Cost through Combination of Artificial Agents CPM and GA

In order to plan a construction project, computer simulations are frequently used to predict the performance of the operations through simulating the process flows and resource selection procedure. However, for finding the optimum resource allocation of the construction activities, all possible combinations must be tested through simulation study. If the number of activities and allocated resources are high, the numbers of these combinations become too large, then this process would not be economical task to do. Therefore, simulation analysis is no longer considered through an optimization technique. Using of Genetic Algorithms (GA) is one of the simple and widely used tools for optimizing heavy intensive engineering problems which can covers various areas of research. With keeping this in mind, this study presented a new hybrid model which integrated agent based modeling with CPM and GA to find out the best resource allocation combination for the construction project’s activities. Based on the results obtained, this new hybrid model can eectively find the optimum resource allocation with respect to time, cost, or any combination of time-cost

A Bayesian approach for seismic recurrence parameters estimation

Recurrence models apply historical seismicity information to seismic hazard analysis. These models that play an important role in the obtained hazard curve are determined by their parameters. Recurrence parameters estimation has some features that lie in missing-data problems category. Thus, the observed data cannot be used directly to estimate model parameters. Furthermore discussion about results reliability and probable conservatism is impossible. The present study aims at offering an approach for Gutenberg-Richter parameters (a and b-values) estimation and determine their variation. Applying the proposed method to analyses of the heterogeneous data sets of seismic catalog, one would calculate valid estimates for recurrence parameters. This method has the capability to reflect all known sources of variability. The results of the case study clearly demonstrate applicability and efficiency of the proposed method, which can easily be implemented not only in advanced but also in practical seismic hazard analyses

Charged System Search and Magnetic Charged System Search Algorithms for Construction Site Layout Planning Optimization

Construction site layout planning can be considered as an effort to place different temporary facilities in available site locations such that multiple objectives are satisfied as much as possible. With the extension of high-rise building construction and construction activities besides the lack of available spaces in construction sites, proper utilization of this resource has been highlighted because of its significant positive influences on direct cost, safety, and security of the site which consequently affects the total cost and schedule of the project. Thus the construction site layout planning is considered as one of the essential and important phases in construction projects. Site layout planning problem is an NP-Hard problem from the viewpoint of complexity. In this research, two prominent meta-heuristic algorithms, namely Charged System Search (CSS) and Magnetic Charged System Search (MCSS) are utilized to optimize the site layout planning problem. The obtained results of implementing these two algorithms for two different types of site space modeling are compared with the results of the Particle Swarm Optimization (PSO) algorithm and also those of the previous studies. The results illustrate the capability of the CSS and MCSS algorithms in solving the present problem

CBO and CSS Algorithms for Resource Allocation and Time-Cost Trade-Off

Resource allocation project scheduling problem (RCPSP) has been one of the challenging subjects among researchers in the last decades. Though several methods have been adopted to solve this problem, however, new metahuristics are available to solve this problem for finding better solution with less computational time. In this paper two new metahuristic algorithms are applied for solving this problem known as charged system search (CSS) and colliding body optimization (CBO). The results show that both of these algorithms find reasonable solutions, however CBO could find the result in a less computational time having a better quality. Two case studies are conducted to evaluate the performance and applicability of the proposed algorithms

A game theory approach for optimum strategy of the owner and contractor in delayed projects

Delay is one of the problems occurring between owners and contractors. Deviation from base plans can be found using project control methods, continuous assessment of the schedule, determining progress percentages and earned value parameters. In such circumstances, conflicts might arise between contractor and owner as restoring project’s original schedule needs added expenditures by the contractor. Moreover, continuation of the previous procedure and late completion of the project will cause the owner damage. In this research, a mathematical model using game theory has been presented. The model investigates the behaviour and strategies of the parties involved in a delayed project through bargaining. It helps owners and contractors gain deeper understanding of the given delay problem, get a fairly accurate analysis of their situation and consider possible strategies in facing with such circumstances without spending a long and inconclusive time. The points which both parties can agree rationally proposed with a numerical example. Results of the model indicate that parameters involved in the problem are effective in changing the range width of negotiation. In special cases, such as disproportionate delay penalty, these parameters even make it neutral in negotiation. Step by step analysis of the model showed which features can threaten negotiation

Cash flow forecasting with risk consideration using Bayesian Belief Networks (BBNS)

Cash-flow management is very important for contractors given that inadequate cash resources typically are the main causes for bankruptcy of construction companies. In comparison to most other industries, the construction industry is severely plagued by risk, and the success of construction projects usually depends on valuating all risks. However, conventional methods suggested by extant research on cash flow forecasting do not consider comprehensive identifica­tion of risk factors, interactions between the factors, and simultaneous occurrences of the factors. This study introduced a simple and appropriate probabilistic cash flow forecasting model using Bayesian Belief Networks (BBNs) to avoid bankruptcy of contractors by considering influence diagrams and risk factors that affect a project. Workability and reli­ability of the proposed approach was tested on an important building construction project in Iran as a real case study, and the results indicated that the model performed well

The Required Compressive Strength and Prehardening Time to Prevent Damage to High Flowing Concrete from Frost Damage at Early Ages

This investigation was undertaken to develop data on the early frost resistance of high flowing concrete made either with various type of mineral fine powders or viscosity agents. From the results of this investigation it was found that the test cylinders cast from air entrained concrete (ie., air>3.5%)which cured up to 23°D.D prior to freezing, performed with satisfactory resistance to early freezing and thawing cycles. However the 28 days strength ratio of all AE specimens were above 100%. This study recommends early continuous protection until AE high flowing concrete has attained compressive strength of 70 to 80 kg/cm^2