Improving construction and demolition waste collection service in an urban area using a simheuristic approach: A case study in Sydney, Australia

Artificial neural network model to predict the compressive strength of eco-friendly geopolymer concrete incorporating silica fume and natural zeolite

Geopolymer concrete (GPC) could be used as an environmental-friendly alternative solution for concrete production due to the detrimental impacts of cement production on the environment. Since obtaining an optimal mix design, and subsequently, predicting the compressive strength of mortar using experimental means is costly and time-consuming, employing soft-computing techniques could facilitate and accelerate this approach. In this research, gene expression programming (GEP) was used to develop numerical models for predicting the compressive strength of GPC based on ground granulated blast-furnace slag (GGBS). Through an experimental program, an extensive database of the compressive strength of GGBS-based GPC consisting of 351 specimens obtained from 117 different mixtures was generated. The five most effective parameters, including specimen age, sodium hydroxide (NaOH) solution concentration, natural zeolite (NZ), silica fume (SF), and GGBS content, were considered as the modeling input parameters. Using GEP algorithm, simplified and practical mathematical equations were proposed to predict the compressive strength of GGBS-based GPC mortar. Performance, high accuracy, and predictability of the proposed equations were validated by the conducted sensitivity and parametric analyses. The obtained results could promote the re-use of GGBS for GPC development, which in turn will lead to environmental and economic advantages.

Compressive strength prediction of eco-efficient GGBS-based geopolymer concrete using GEP method

Industrial information integration engineering (IIIE) is a set of foundational concepts and techniques that facilitate the industrial information integration process. In recent years, many applicat...

A Survey on Industrial Information Integration 2016–2019

Geopolymer concrete (GPC), usually produced via the activation of the cementitious nature of industrial by-products (IBPs) such as ground granulated blast furnace slag (GGBFS) and fly ash (FA), has potential to be used as a replacement for conventional portland concretes (CPCs). In this study, the effect of the concentration of sodium hydroxide (NaOH) and substitution of GGBFS with pozzolans such as natural zeolite (NZ) and silica fume (SF) on the mechanical properties of GPC was investigated experimentally. For this purpose, the compressive, flexural, and tensile strengths of various GPC mixes were measured. GPC mixes were prepared with various concentrations (i.e., 4, 6, and 8 M) of sodium hydroxide as well as GGBFS substitution (i.e., 5, 10, 15, 20, 25, and 30 wt%) with NZ and SF. Furthermore, the response surface method (RSM) was employed to achieve the optimum values of the design variables to maximize the compressive, flexural, and tensile strengths of pozzolanic GGBFS-based GPC. Overall, the results showed that with increasing NaOH concentration, the compressive strength was decreased while the maximum flexural and tensile strengths were obtained when the concentration of NaOH was 6 M compared with 4 and 8 M. In addition, the utilization of NZ improved the compressive, flexural, and tensile strengths of GGBFS-based GPC by about 4%, 6%, and 20%, respectively, at 10 wt% replacement. Moreover, the substitution of GGBFS with SF could improve the compressive, flexural, and tensile strengths of GPC up to 30%, 20%, and 25%, respectively, at 30 wt% substitution. Besides, the optimization results demonstrated that by substituting GGBFS with 60.29 kg (i.e., 15.9%) of NZ and using 5.28 M NaOH the optimal trinary conditions in terms of the compressive, flexural, and tensile strength values could be achieved. The optimal conditions could also be obtained by substituting GGBFS with 113.79 kg (i.e., 30.0%) of SF and using 6.19 M NaOH.

Mechanical properties of GGBFS-based geopolymer concrete incorporating natural zeolite and silica fume with an optimum design using response surface method

Reliability estimation using an integrated support vector regression – variable neighborhood search model

This paper concerns with the integration of rough set theory with the Best Worst method to evaluate information system performance within supplier selection problem of biofuel companies. First, a set of main criteria and sub-criteria are collected and then to include uncertainty in decision making, rough set theory is employed. The rough best worst method is applied for weighing and supplier evaluation with respect to information system performance and environmental impacts. Further, a case study is conducted for biofuel company supplier selection and the results imply the effectiveness of the approach in tactical performance evaluation. The best criteria effective on the green supplier selection of ISs performance is determined to be Quality.

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Rough Best-Worst Method for Supplier Selection in Biofuel Companies based on Green criteria

Information Systems (IS) have become crucial for all the organizations to survive in contemporary technology-oriented environment. Consequently, the number of companies and organizations which have invested widely in their IS infrastructures to present better services and to produce higher value products is increasing. On the other hand, nowadays, because of the increase of governmental rules and serious requirements of more people in the case of environmental protection, it seems necessary for all the enterprises to follow these regulations if they want to survive in the global markets. However, what is at issue here is not just the companies’ agreement with the environmental laws; in addition, they should apply some strategies to decrease the negative environmental impacts of their products in some countries. Thus, the aforementioned arguments are the reasons for the compulsory use of the green supplier selection (GSS) in all firms. Considering the mentioned contents, the purpose of this study is representation of the relation between ISs and GSS as two vital components of firms in a novel way which has not been done before. Actually, it shows the ISs' performance or effectiveness to select the green suppliers taking into account the different levels of importance of GSS measures (including eight criteria and 31 sub-criteria), using a multi-criteria decision-making method called Best Worst Method (BWM) to identify the weights (importance) of GSS measures and compute the GSS performance of 10 ISs in a company using the data gathered in a survey from ISs' experts.

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Green supplier selection based on the information system performance evaluation using the integrated best-worst method

\nPurpose\nHowever, due to the huge number of studies and on the other hand to be new and creative, the represented models and methods – as the two main parts of this field – have been got more complicated, which consequently have been turned into unpractical research studies for the realistic situations. Therefore, the purpose of this study is the representation of a novel and simple method to deal with the aforementioned gap.\n\n\nDesign/methodology/approach\nTo this end, Fazl-Tash method have been proposed, in which a thorough and complete model including 114 criteria and a simple technique to rank and select the best supplier have been presented. Sustainability and resiliency are considered in collecting criteria effective on supplier selection.\n\n\nFindings\nThe method was carried out in a case study in an industrial company. The efficiency of the proposed method is evaluated in comparison with other conventional approaches.\n\n\nOriginality/value\nAs selecting the supplier plays a crucial role to bring some important advantages for companies, such as coping with the cost and time problems and influencing the majority of contemporary markets’ requirements, in recent years, there have been representing more effective studies in the supplier selection literature.\n

Design of Fazl-Tash novel method for sustainable resilient comprehensive supplier selection problem

Information Systems (IS) have turned into vital means for companies to survive in the contemporary technology-oriented environment. Subsequently, over the last decades, this has brought about the heavy investment of companies in ISs to guarantee high-quality products and services. Similarly, supplier selection (SS) plays an inescapable role in today’s business. In addition, there are several studies published showing the importance of the ISs in the SS problem. However, there has not been any work evaluating the effectiveness of ISs on the SS problem, including a comprehensive and up-to date SS model. Therefore, this study proposed a complete model including six criteria that are almost most important and shared in the literature: sustainability, reliability, resiliency, greenness, risk and cost, and 31 sub-criteria. Then the effectiveness of 10 ISs on the SS problem has been shown through using BWM in two consecutive stages, and then the model conducted in Emdadkhodro automotive company to show its practicality and accuracy.

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Navid Kazemitash

Papers

Reliability estimation using an integrated support vector regression – variable neighborhood search model

Rough Best-Worst Method for Supplier Selection in Biofuel Companies based on Green criteria

Green supplier selection based on the information system performance evaluation using the integrated best-worst method

Design of Fazl-Tash novel method for sustainable resilient comprehensive supplier selection problem

A Multidimensional Decision Making for Supplier Selection in the presence of Information Systems