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This research attempts to present a solid transportation problem (STP) mechanism in uncertain and indeterminate contexts, allowing decision makers to select their acceptance, indeterminacy and untruth levels.

Due to the lack of reliable information, changeable economic circumstances, uncontrolled factors and especially variable conditions of available resources to adapt to the real situations, the authors are faced with a kind of uncertainty and indeterminacy in constraints and the nature of the parameters of STP. Therefore, an approach based on neutrosophic logic is offered to make it more applicable to real-world circumstances. In this study, the triangular neutrosophic numbers (TNNs) have been utilized to represent demand, transportation capacity, accessibility and cost. Then, the neutrosophic STP was converted into an interval programming problem with the help of the variation degree concept. Then, two simple linear programming models were extracted to obtain the lower and upper bounds of the optimal solution.

The results reveal that the new model is not complicated but more flexible and more relevant to real-world issues. In addition, it is evident that the suggested algorithm is effective and allows decision makers to specify their acceptance, indeterminacy and falsehood thresholds.

Under the transportation literature, there are several solutions for TP and STP in crisp, fuzzy set (FS) and intuitionistic fuzzy set (IFS) conditions. However, the STP has never been explored in connection with neutrosophic sets to the best of the authors’ knowledge. So, this work tries to fill this gap by coming up with a new way to solve this model using NSs.

The main purpose of this paper is to create a suitable structure based on neutrosophic numbers to evaluate the safety performance in construction projects in such a way that the shortcomings can be highlighted with the reasoned measurement and possible strategies can be recommended.

Data envelopment analysis (DEA), which is a useful tool for performance appraisal, along with neutrosophic logic, which is one of the most complete tools for handling uncertainty phenomenon, has been used to evaluate the safety performance of construction projects. With this hybrid model, a new strategy is considered as an indicator for safety performance and comparisons are made between different units.

A total of 35 Chinese organizations with construction projects lasting between 1.5 and 2 years were selected for comparison. After processing the data into neutrosophic numbers and using the NN-DEA model, it can be found that projects that pay more attention to safety issues such as training and equipment are more efficient.

Since in the real world, there are uncertainties with different contradictions, and neutrosophical data can handle many of these challenges, using DEA model with neutrosophic numbers to evaluate the performance of construction projects from a safety perspective, can provide significantly better results. Therefore, considering that no study has been presented in this field so far, the authors will deal with this topic.

Modern construction methods have been developed with the goal of reducing construction time as much as possible, which results in some situations during construction and within the first few days after it, when concrete is subjected to exceptionally high loads. The precast concrete, which is the concrete in very early ages, may result in severe cracks or damages. In conventional construction projects, sometimes working with concrete, which had not reached its ultimate strength, is an unavoidable matter of fact. This paper aims to discuss these issues.

Researchers in the field of construction materials have done their best to make some changes in the different parts of the concrete in order to bring about reforms, based on the existing needs, and achieve new quality and primacy from concrete. One kind of concrete, the emergence of which dates back to many years ago, is self-compacting concrete. Thanks to its high efficiency for the parts with complex forms of high-density steel, this kind of concrete suggests new prospects.

This study aims at evaluating the effect of early loads on the 28-day compressive strength of concretes with zeolite and limestone powder under different curing conditions (wet or dry). In this regard, two self-compacting concrete mix designs with the same ratio of water to cementations materials and 0.4 percent and 10 percent zeolite have been considered; therefore, concrete cube samples with zeolite and limestone powder in different curing conditions at ages of three, one and seven days under preloading with 80–90 percent of compressive strength are damaged, and after curing in different conditions, their 28-day compressive strength is measured. According to the results, the recovery of the 28-day compressive strength of damaged samples, compared to that of intact samples, is possible in all curing conditions. The experiments that have been performed on concrete samples under dry and wet curing conditions show that the full recovery of compressive strength of damaged samples compared to that of intact ones happened only in preloaded samples at the age of one days, and in other ages (three and seven days) the 28-day strength reduction has occurred in damaged samples compared to the that in intact samples. The results of concrete samples with zeolite and without limestone powder at the age of one day indicate the greatest impact on other samples on the 28-day compressive strength of damaged samples compared to that of intact ones, occurring under dry condition.

This research analyzed and studied the influence under wet and dry curing conditions and the presence of limestone powder and zeolite fillers in recovering of the 28-day compressive strength of preloaded concrete samples at early stages (one, three and seven days) after the construction of the concrete.

The purpose of this paper is to investigate the effect of steel and carbon fibers on the mechanical properties of light concrete in terms of tension strength, compressive strength and elastic modulus under completely dry and wet conditions.

In this study, the lightweight concrete made of Light Expanded Clay Aggregate (LECA) as coarse aggregate and sand as fine aggregate was used. To achieve a compressive strength of at least 20 MPa, microsilica was used 10 percent by weight of cement. In order to compensate for the reduction of tension strength of concrete, steel and carbon fibers were used with three volume ratio of 0.5, 1 and 1.5 percent in concrete. The results of concrete specimens were studied at the age of 7, 28, 42 and 90 days under controlled dry and wet conditions.

The results showed that the addition of steel and carbon fibers to the concrete mixture would reduce the drop in slump. Also, the use of steel and carbon fibers plays a significant role in increasing the tension strength of the specimens. Furthermore, the highest increase in tension strength of steel and carbon fiber samples was 83.3 and 50 percent, respectively, than the non-fibrous specimen when evaluated at 90 days of age. Moreover, the steel and carbon fiber increased the water absorption of the samples. Adding steel and carbon fibers to a lightweight concretes mixture containing LECA aggregates plays a significant role in increasing the modulus of elasticity of the samples. The highest increase in the elastic modulus of steel and carbon fibers was 18.9 and 35.4 percent, respectively, than the non-fibrous specimen at 28 days of age.

In this paper, the authors investigated the mechanical properties of steel fiber and carbon reinforced concrete. Also, according to the conditions of storage of samples and the age of concrete (day), the experiments were carried out on samples.

The purpose of this paper is to present the efficient iterative methods for solving linear complementarity problems (LCP), using a class of pre-conditioners.

By using the concept of solving the fixed-point system of equations associated to the LCP, pre-conditioning techniques and Krylov subspace methods the authors design some projected methods to solve LCP. Furthermore, within the computational framework, some models of pre-conditioners candidates are investigated and evaluated.

The proposed algorithms have a simple and graceful structure and can be applied to other complementarity problems. Asymptotic convergence of the sequence generated by the method to the unique solution of LCP is proved, along with a result regarding the convergence rate of the pre-conditioned methods. Finally, a computational comparison of the standard methods against pre-conditioned methods based on Example 1 is presented which illustrate the merits of simplicity, power and effectiveness of the proposed algorithms.

Comparison between the authors' methods and other similar methods for the studied problem shows a remarkable agreement and reveals that their models are superior in point of view rate of convergence and computing efficiency.

For solving LCP more attention has recently been paid on a class of iterative methods called the matrix-splitting such as AOR, MAOR, GAOR, SSOR, etc. But up to now, no paper has discussed the effect of pre-conditioning technique for matrix-splitting methods in LCP. So, this paper is planning to fill in this gap and the authors use a class of pre-conditioners with iterative methods and analyze the convergence of these methods for LCP.

In this paper, a combined TODIM-BSC method with the neutrosophical approach for evaluating the performance of a private insurance company has been proposed. In other words, first, using the BSC technique, and identify the performance evaluation indicators, then evaluate the performance of the insurance company's agencies and rank them with the TODIM decision-making method.

The insurance industry has a special prestige and importance in domestic and foreign trade. The evaluation of insurance companies, in addition to informing the stakeholders, increases competition, industry dynamism, sustainable and balanced development of society. The purpose of this paper is to establish a model for evaluating the performance of private insurance companies by adopting multiple-attribute decision-making and Balanced Scorecard (BSC) with single-values neutrosophic numbers (SVNNs) which will be applied by considering a set of indicators and alternatives deliberated with different viewpoints.

A case study of the private insurance agencies in one of the provinces of Iran based on 26 criteria of agencies is used to confirm the practicality and effectiveness of the proposed model. Finally, there was a discussion about why the results are logical, which shows the strength and robustness of the proposed framework.

To the best of our knowledge, no study has been performed to evaluate the performance of a real-world problem with the integrated TODIM-BSC method in a neutrophilic environment. Therefore, this paper can be effective in bridging the existing research gap and expanding our knowledge of the discussion of evaluating the performance of organizations or companies. Besides, by using these results, the authors can help the planners of these companies as well as similar organizations in attracting satisfaction and retaining target customers.

Entrepreneurship as a development engine has a distinct character in the economic growth of countries. Therefore, governments must support entrepreneurship in order to succeed in the future. The best way to improve the performance of this entrepreneurial advocacy is through efficient measurement methods. For this reason, the purpose of this paper is to propose a new integrated dynamic multi-attribute decision-making (MADM) model based on neutrosophic set (NS) for assessment of the government entrepreneurship support.

Due to the nature of entrepreneurship issues, which are multifaceted and full of uncertain, indeterminate and ambiguous dimensions, this measurement requires multi-criteria decision-making methods in spaces of uncertainty and indeterminacy. Also, due to the change in the size of indicators in different periods, researchers need a special type of decision model that can handle the dynamics of indicators. So, in this paper, the authors proposed a dynamic neutrosophic weighted geometric operator to aggregate dynamic neutrosophic information. Furthermore, in view of the deficiencies of current dynamic neutrosophic MADM methods a compromised model based on time degrees was proposed. The principle of time degrees was introduced, and the subjective and objective weighting methods were synthesized based on the proposed aggregated operator and a nonlinear programming problem based on the entropy concept was applied to determine the attribute weights under different time sequence.

The information of ten countries with the indicators such as connections (C), the country's level of education and experience (EE), cultural aspects (CA), government policies (GP) and funding (F) over four years was gathered and the proposed dynamic MADM model to assess the level of entrepreneurial support for these countries. The findings show that the flexibility of the model based on decision-making thought and we can see that the weights of the criteria have a considerable impact on the final evaluations.

In many decision areas the original decision information is usually collected at different periods. Thus, it is necessary to develop some approaches to deal with these issues. In the government entrepreneurship support problem, the researchers need tools to handle the dynamics of indicators in neutrosophic environments. Given that this issue is very important, nonetheless as far as is known, few studies have been done in this area. Furthermore, in view of the deficiencies of current dynamic neutrosophic MADM making methods a compromised model based on time degrees was proposed. Moreover, the presented neutrosophic aggregation operator is very suitable for aggregating the neutrosophic information collected at different periods. The developed approach can solve the several problems where all pieces of decision information take the form of neutrosophic information collected at different periods.

Knowledge management (KM) significantly affects supply chain management (SCM) and its performance in today's highly competitive corporate climate. It is crucial to consider this relationship to achieve optimal supply chain performance (SCP). This study aims to assess this impact by defining and examining the multi-dimensional relationships between KM Process Elements (KMPEs) and SCP Evaluation Criteria (SCPEC) within a comprehensive theoretical framework.

Integrating KMPEs and SCPEC becomes an uncertain decision-making problem due to data deficiency and the vagueness of decision-makers’ judgments. To address uncertainties, this study uses interval-valued neutrosophic (IVN) sets and proposes an IVN model consisting of SWARA, which is one of the effective multi-criteria decision-making (MCDM) approaches, and house of quality (HOQ) methods. IVN-SWARA is used to weight the SCPEC while IVN-HOQ establishes relationships and prioritizes the KMPEs and SCPEC.

The results show that reliability is the most significant SCP evaluation criterion. Among the KMPEs, capitalization, sharing, and transfer exhibit stronger associations with the SCPEC compared to the other elements. Capitalization as one of the KMPEs was found to be the most critical one, and efficiency is the criterion most affected by all elements of the KM process.

This study uses innovative methodologies to evaluate the adoption of KM processes on SCP under uncertain environments and involving multi-decision-makers. The proposed integrated model demonstrates flexibility and practicality in combining KM and SCM, leading to improved SCP. Notably, this study presents the development of IVN-SWARA and the use of the integrated IVN-SWARA - IVN-HOQ decision tool, which are novel contributions to the existing literature.

Sustainable supply chain management (SSCM) practices and policies are necessary for businesses that seek to take part in international markets and ensure any form of competitiveness. Over time, and especially in the recent past, researchers, governments, and other policymakers have made use of broad and systematic approaches and come to appreciate the value-enhancing activities of sustainability.

Businesses have embraced the integration of sustainable policies and practices within the supply chain as a critical step in ensuring the efficiency of their operations. It is clear in previous studies and operational programs of enterprises that SSCM practices accord businesses certain benefits including improving their environmental, social, and economic performance, and increasing their ecological awareness by way of influencing performance elements within supply networks in enterprises. The study examines the factors influencing performance and theories of SSCM using a neutrosophic method in the textile industry.

SSCM performance is thus of great importance in ensuring business success and competitiveness, realizing customer satisfaction, and leaving the environment in a desirable state for future generations. Performance management, by assisting in the decision-making by managers and ensuring an adequate level of internal interaction, is an integral part of assimilating sustainability management into businesses. SSCM theories also have a strong impact on the determination of the sources of competitive advantage through effective utilization of business capabilities to solve environmental and social challenges that may affect business performance.

In line with the benefits highlighted, this study seeks to evaluate and select the factors affecting SSCM performance and theory in textile enterprises with corporate identity in Ordu and Giresun provinces following a neutrosophic approach. To this end, the elements obtained from the literature review are evaluated using the MULTIMOORA-mGqNN method.