Sharif Digital Repository

There are two strategies for deadlock handling in routing algorithms in NoC: deadlock avoidance and deadlock recovery. Some deadlock recovery routing algorithms are re-injection based, such as: Compressionless (CR), Software-Based (SW-TFAR) and AFBAR. In spite of the performance comparison, none of existing researches have focused on the energy consumption of various routing algorithms. We evaluate these routing algorithms according to their energy consumption and latency. Our experimental results show the better performance and worse energy consumption of deadlock recovery routing algorithms compared to deadlock avoidance routing algorithms. In addition, the best and worst energy... 

In this research, an adsorbent with manifold interplay sites for the adsorption of sulfur components is developed in a silver ion functionalized Cr3+ based metal-organic framework (MIL-101(Cr)-SO3Ag). The adsorption performance of MIL-101(Cr), MIL-101(Cr)-SO3H, and MIL-101(Cr)-SO3Ag was evaluated in dynamic adsorption system in terms of its adsorption capacity. MIL-101(Cr)-SO3Ag could interact with H2S through multiple ways which performed about 4 times higher adsorption capacity (96.75 mg/g) rather than MIL-101(Cr); further, the high adsorption capacity of MIL-101(Cr)-SO3Ag was almost unchanged after five successive adsorption–desorption cycles, making it a potential adsorbent for an... 

The growing rate of population and technological advancement have led to an increase in natural resource consumption, which has caused irreparable damage to the environment. The implementation of green supply chain management is one of the most effective ways to deal with environmental degradation. Therefore, in this paper, a bi-objective mixed integer linear programming model is developed to design a green supply chain network. In the proposed model, the possibility of customer storage, being faced with shortage, locating of distribution centres, green vehicle routing problem, split delivery, multi-depot vehicle routing problem (VRP), capacitated VRP, and uncertainty in demands will be... 

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier... 

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier... 

In the eld of supply chain, selecting a suitable green supplier could signi cantly help us decrease the cost and risks of the operations and increase the quality of green supply. This paper develops an integrated two-stage approach based on Fuzzy Analytic Hierarchy Process (FAHP) and multi-objective mixed-integer linear programming to select suppliers and allocate order in the green supply chain. In the rst stage, suppliers are evaluated using FAHP method and in the second stage, a multi-product multi-period supply chain is developed considering green location-routing problem, discounting, and time window under uncertainty. Then, a fuzzy solution approach is applied to solve the proposed... 

Hybrid composites of MIL-101(Cr) and Nanoporous Graphene with ratios in the range of 10–50% were prepared via hydrothermal synthesis method. This study deals with an experimental investigation on selective oxidation of H2S into elemental sulfur in the range of 200–270 °C, the catalyst activity and selectivity toward sulfur was studied. High-temperature reactor tests indicated that the MIL-101(Cr)–NPG50–Mo could be a promising candidate with conversion and selectivity of 100% and 99.5% at 200 °C. The MIL-101(Cr)–NPG50–Mo stability showed there were not any significant changes in physical properties, the activity was evaluated after 20 h which was completely stable without any changes  

The increasing level of customer awareness and application of environmental laws by governments, on the one hand, and the increasing number of competitors, on the other hand, has obliged industry owners to include green activities in the design of the supply chain network. Green activities include any type of action that reduces environmental degradation. Hence, this study seeks to develop a bi-objective, mixed integer linear programming (MILP) model for designing a green supply chain network. In the proposed model, the minimisation of costs and detrimental environmental effects are discussed. LP metric method is used to solve the bi-objective model and the proposed model is run by using... 

Maximizing the value of resources and producing less waste are strategic decisions affecting sustainability and competitive advantage. Sustainable closed-loop supply chains (CLSCs) are designed to minimize waste by circling back (repairing, reselling, or dismantling for parts) previously discarded products into the value chain. This study presents a novel two-stage fuzzy supplier selection and order allocation model in a CLSC. In Stage 1, we use the fuzzy best-worst method (BWM) to select the most suitable suppliers according to economic, environmental, social, and circular criteria. In Stage 2, we use a multi-objective mixed-integer linear programming (MOMILP) model to design a... 

Municipal solid waste (MSW) directly impacts community health and environmental degradation; therefore, the management of MSW is crucial. Medical waste is a specific type of MSW which is generally divided into two categories: infectious and non-infectious. Wastes generated by coronavirus disease 2019 (COVID-19) are classified among infectious medical wastes; moreover, these wastes are hazardous because they threaten the environment and living organisms if they are not appropriately managed. This paper develops a bi-objective mixed-integer linear programming model for medical waste management during the COVID-19 outbreak. The proposed model minimizes the total costs and risks, simultaneously,... 

Maximizing the value of resources and producing less waste are strategic decisions affecting sustainability and competitive advantage. Sustainable closed-loop supply chains (CLSCs) are designed to minimize waste by circling back (repairing, reselling, or dismantling for parts) previously discarded products into the value chain. This study presents a novel two-stage fuzzy supplier selection and order allocation model in a CLSC. In Stage 1, we use the fuzzy best-worst method (BWM) to select the most suitable suppliers according to economic, environmental, social, and circular criteria. In Stage 2, we use a multi-objective mixed-integer linear programming (MOMILP) model to design a... 

Many cities are struggling to keep pace with limited budgets and rapid growth. Economic development models involving public-private partnerships (P3s) can help drive economic revitalization. The choice of partners plays a vital role in the success or failure of sustainable P3 initiatives. In this study, we propose a novel integrated sustainable private partner selection framework in P3s. The proposed model is composed of the best-worst method (BWM), the weighted influence non-linear gauge system (WINGS), and the technique of order preference similarity to the ideal solution (TOPSIS). The BWM is used to identify the importance weights of the economic, environmental, social, and technological... 

In the real world, there are complex decision-making problems in which a variety of intertwined factors and hierarchical structures exist, and it is difficult or impossible to solve these problems using classical methods. The prioritization of circular economy (CE) adoption barriers is one such complex problem that cannot be solved using current classical methods. Hence, in this paper, for the first time, a new method, namely, FBWDS, is developed. FBWDS derives from the combination of fuzzy best–worst method (BWM), fuzzy decision-making trial and evaluation laboratory (DEMATEL), and Supermatrix structure. This proposed method establishes weights of the intertwined factors in hierarchical... 

The tourism and hospitality industry significantly impacts socio-economic development and cultural growth in developing countries. This study develops an integrated multicriteria decision-making and optimization model for partner selection in public-private partnership (PPP) projects in the hospitality industry. The proposed model uses a weighted influence non-linear gauge system to evaluate the partners. A multi-objective optimization model is then utilized to select a partner for each PPP project using a linear programming metric solution approach. A case study demonstrates the applicability of the proposed model in a PPP project in Iran to renovate and convert historic houses into hotels...