Integrated supplier selection framework in a resilient construction supply chain: An approach via analytic hierarchy process (AHP) and grey relational analysis (GRA)

Construction supply chain management is a unique and problematic issue within the construction industry due to its inevitable external risks and variations. The resilience capability of a supplier is of significance in supplier selection; a supplier selected in the context of a resilient construction supply chain (RCSC) is referred to in this research as a "resilient construction supplier". This paper proposes a supplier selection framework tailored to effective information integration for supply chain management. The proposed framework works by integrating building information modeling (BIM) and a geographic information system (GIS) in a RCSC. BIM and GIS together provide highly transparent construction material information, enhanced supply chain status visualization, and workable access information for supplier selection. Supplier performance is evaluated via seventeen resilient criteria under a combined methodology consisting of the analytic hierarchy process (AHP) and grey relational analysis (GRA); AHP and GRA weigh the criteria and rank the suppliers respectively. By varying the weightings given to each criterion, sensitivity analysis was conducted to identify the criteria of resilience which impact the selection priorities of suppliers. An illustrative example is also provided to show the overall process of the proposed framework

A portable BRCA1-HAC (human artificial chromosome) module for analysis of BRCA1 tumor suppressor function

BRCA1 is involved in many disparate cellular functions, including DNA damage repair, cell-cycle checkpoint activation, gene transcriptional regulation, DNA replication, centrosome function and others. The majority of evidence strongly favors the maintenance of genomic integrity as a principal tumor suppressor activity of BRCA1. At the same time some functional aspects of BRCA1 are not fully understood. Here, a HAC (human artificial chromosome) module with a regulated centromere was constructed for delivery and expression of the 90 kb genomic copy of the BRCA1 gene into BRCA1-deficient human cells. A battery of functional tests was carried out to demonstrate functionality of the exogenous BRCA1. In separate experiments, we investigated the role of BRCA1 in maintenance of heterochromatin integrity within a human functional kinetochore. We demonstrated that BRCA1 deficiency results in a specific activation of transcription of higher-order alpha-satellite repeats (HORs) assembled into heterochromatin domains flanking the kinetochore. At the same time no detectable elevation of transcription was observed within HORs assembled into centrochromatin domains. Thus, we demonstrated a link between BRCA1 deficiency and kinetochore dysfunction and extended previous observations that BRCA1 is required to silence transcription in heterochromatin in specific genomic loci. This supports the hypothesis that epigenetic alterations of the kinetochore initiated in the absence of BRCA1 may contribute to cellular transformation

Efficient safety information retrieval on construction sites: A preliminary methodology

IT-supported field data management benefits on-site construction management by improving accessibility to the information and promoting efficient communication between project team members. However, most of on-site safety inspections still heavily rely on subjective judgment and manual reporting processes and thus observers’ experiences often determine the quality of risk identification and control. This study aims to develop a methodology to efficiently retrieve safety-related information so that the safety inspectors can easily access to the relevant site safety information for safer decision making. The proposed methodology consists of three stages: (1) development of a comprehensive safety database which contains information of risk factors, accident types, impact of accidents and safety regulations; (2) identification of relationships among different risk factors based on statistical analysis methods; and (3) user-specified information retrieval using data mining techniques for safety management. This paper presents an overall methodology and preliminary results of the first stage research conducted with 101 accident investigation reports

An information model for subcontractor resource allocation

textSubcontractors perform the majority of the work on commercial construction projects. However, only limited research has focused on subcontractors’ practical needs. In response, this research discovered and documented subcontractor needs through data collections and extended these findings with development of an information model and tool. This research significantly enlarges detailed understanding of subcontractor management practices, in particular around resource allocation across multiple projects. While existing research has shown the importance of multi-project management, exploration of details of this process has largely been limited to overviews of policies. Rich details that allow for specific critiques of existing methods and tools have been missing. This research provides such details, including specific limitations and recommendations to existing information standards, commercial applications, and assignment algorithms. In particular, contributions of this research focus on support for what-if analysis under extreme frequency of resource reallocation, a limitation of existing tools and methods that make them unsuitable for most subcontractors.Civil, Architectural, and Environmental Engineerin

Development of a Nonlinear Integer Optimization Model for Tenant Mix Layout in a Shopping Centre

The tenant mix layout of shopping malls affects shopper consumption behaviour and the performance of malls. The main function of the tenant mix layout is to increase store sales by increasing footfall. However, although existing studies have shown the importance of the spatial clustering effect and the physical information about tenants, the authors of those studies did not properly consider both the spatial clustering effect and the physical information about tenants at the meantime. Through this study, we aimed to maximize the spillover effect of the stores in the shopping centre while considering both the spatial clustering effect and physical information about tenants. Therefore, we present a problem called the tenant mix problem, which is to determine the optimal tenant configuration scheme for existing shopping centre space segmentation to maximize the rental income of a shopping centre. To solve this problem, a nonlinear integer optimization model with defined characteristics was proposed and solved using a genetic algorithm. A shopping centre case study is also presented to verify the performance of the model

Generative design of floor plans of multi-unit residential buildings based on consumer satisfaction and energy performance

Satisfying consumers is an important task in the design of residential floor plans. However, the design of residential floor plans with the aim of improving consumer satisfaction and energy performance has not been fully explored. Also, the preferences of different customer groups regarding customer satisfaction have not been studied. Traditional design and optimization methods still have limitations in terms of performance improvement, while performance-based generative design methods can explore the performance improvement potential of a larger range of solution spaces. Therefore, this study introduces a generative design framework that is grounded on optimizing energy performance and consumer satisfaction for multi-unit residential floor plans, which consists of four main processes: 1) Generation of floor plan schemes. 2) Evaluation of consumer satisfaction and energy performance of the generated schemes. 3) Running a multi-objective optimization to obtain optimal schemes. 4) The final floor plan scheme is determined by the decision maker. The proposed framework was employed in a real design case, and seven optimal solutions were obtained. Compared with the initial scheme, the maximum improvement in consumer satisfaction and energy performance was up to 38.78% and 11.18% respectively. The results also indicated that the preferences of different types of consumers differed significantly. Thus, different evaluation functions have been created to provide solutions with higher satisfaction levels targeting different types of consumers. As such, generative design and optimization of residential floor plans for specific types of consumers can be undertaken at an early design stage to improve consumer satisfaction and reduce energy consumption

An Investment Decision Model for Underground Urban Utility Tunnel Based on MIVES and Real Option Theory from a Sustainable Perspective

Although the importance of urbanization, urban renewal and sustainable development have been increasingly recognized, with the accelerating process of urbanization, the urban above-ground space is no longer sufficient for the process of urbanization, and downward development of the city has become inevitable. Underground Urban Utility Tunnel (UUUT) is an effective measure to promote the sustainable development of urban underground space (UUS). However, decision makers still cannot fully consider the economic, social, environmental and technological factors, as well as the future risks of the project and the value of flexibility in management. In this paper, an investment decision model for UUUT is proposed that combines the Integrated Value Model for Sustainable Assessment (MIVES) and the real option theory, which comprehensively considers the social, economic, environmental and technological impacts, and assists the government in carrying out the investment decision analysis of UUUT from a sustainability perspective by applying the real option theory to the economic evaluation process. The primary process of this study can be divided into four steps. (1) establishment of the investment decision index system for UUUT; (2) determination of the quantitative criteria for each indicator; (3) calculation of the feasibility of UUUT; and (4) a case study to demonstrate the feasibility of the proposed model, as well as the achieved results. The proposed investment decision model can be used as an auxiliary tool in the early planning stage of UUUT, and also for the comparison and selection of different options for UUUT

Smart Project Management: Interactive Platform Using Natural Language Processing Technology

Technological developments have made the construction industry efficient. The aim of this research is to solve communication interaction problems to build a project management platform using the interactive concept of natural language processing technology. A comprehensive literature review and expert interviews associated with techniques dealing with natural languages suggests the proposed system containing the Progressive Scale Expansion Network (PSENet), Convolutional Recurrent Neural Network (CRNN), and Bi-directional Recurrent Neutral Networks Convolutional Recurrent Neural Network (BRNN-CNN) toolboxes to extract the key words for construction projects contracts. The results show that a fully automatic platform facilitating contract management is achieved. For academic domains, the Contract Keyword Detection (CKD) mechanism integrating PSENet, CRNN, and BRNN-CNN approaches to cope with real-time massive document flows is novel in the construction industry. For practice, the proposed approach brings significant reduction for manpower and human error, an alternative for settling down misunderstanding or disputes due to real-time and precise communication, and a solution for efficient documentary management. It connects all contract stakeholders proficiently