An integrated model for product mix problem and scheduling considering overlapped operations

Product mix problem is one of the most important decisions made in production systems. Several algorithms have been developed to determine the product mix. Most of the previous works assume that all resources can perform, simultaneously and independently, which may lead to infeasibility of the schedule. In this paper, product mix problem and scheduling are considered, simultaneously. A new mixed-integer programming (MIP) model is proposed to formulate this problem. The proposed model differentiates between process batch size and transfer batch size. Therefore, it is possible to have overlapped operations. The numerical example is used to demonstrate the implementation of the proposed model. In addition, the proposed model is examined using some instances previously cited in the literature. The preliminary computational results show that the proposed model can generate higher performance than conventional product mix model

A Comprehensive Study on the Expansion of Electric Vehicles in Europe

Funding: This research received no external funding.Peer reviewedPublisher PD

Association of glutathione S-transferase polymorphisms with the severity of mustard lung

Introduction: Glutathione S-transferase (GST) is one of the major detoxifiers in alveoli. Polymorphism in GST genes can influence the ability of individuals to suppress oxidative stress and inflammation. The present study was aimed to explore the hypothesis that the genetic polymorphisms of GST T1, M1 and P1 are associated with the severity of the mustard lung in the sulfur mustard-exposed individuals. Methods: Blood samples were taken from 185 sulfur mustard-exposed and 57 unexposed subjects. According to the stage of the mustard lung, sulfur mustard-exposed patients were categorized in the mild/moderate and severe/very severe groups. A multiplex PCR method was conducted to identify GSTM1 and GSTT1 null genotypes. To determine the polymorphisms of GSTP1 in exon 5 (Ile105Val) and exon 6 (Ala114Val), RFLP-PCR method was performed. Results: The frequency of GSTM1 homozygous deletion was significantly higher in the severe/very severe patients compared with the mild/moderate subjects (66.3% vs. 48%, P = 0.013). The GSTM1 null genotype was associated with the severity of mustard lung (adjusted odds ratio [OR], 2.257; 95% CI, 1.219-4.180). There was no significant association between GSTT1 and GSTP1 polymorphisms with the severity of the mustard lung. Conclusion: The different distribution of GSTM1 null genotype in severe/very severe and mild/moderate groups indicated that the severity of the mustard lung might be associated with the genetic polymorphism(s)

A Comprehensive Study on the Expansion of Electric Vehicles in Europe

There has been a rapid increase in government efforts to expand electric vehicle markets by deploying fast-charging stations, promoting uptake through greater investment, and by enacting supportive policies. Government support and private investment have contributed to the expansion of electric vehicles in many countries. The aim of this study is to highlight and analyze the most critical aspects of the expansion of the electric vehicle market, regarding technologies, characteristics, advantages and disadvantages, opportunities, and barriers in Europe. Our study analyzes the progress of electric vehicles by reviewing recent literature based on technology, policy, and government measurements. This study provides comprehensive information on electric vehicles and perspectives that are critical to policymakers, car manufacturers, consumers, and the community. To achieve favorable results, governments should invest in developing electric vehicles and battery technologies, provide subsidies, and develop charging infrastructure. Furthermore, by analyzing current EV sales in ten countries around the world, we assess the operating costs of electric vehicles. Overall EV cost of ownership is influenced by grid electricity price, cost of financing, location, carbon tax, wind speed, and solar insolation

Indoor environment assessment of special wards of educational hospitals for the detection of fungal contamination sources: A multi-center study (2019-2021)

Background and Purpose: The hospital environment was reported as a real habitat for different microorganisms, especially mold fungi. On the other hand, these opportunistic fungi were considered hospital-acquired mold infections in patients with weak immune status. Therefore, this multi-center study aimed to evaluate 23 hospitals in 18 provinces of Iran for fungal contamination sources.Materials and Methods: In total, 43 opened Petri plates and 213 surface samples were collected throughout different wards of 23 hospitals. All collected samples were inoculated into Sabouraud Dextrose Agar containing Chloramphenicol (SC), and the plates were then incubated at 27-30ºC for 7-14 days.Results: A total of 210 fungal colonies from equipment (162, 77.1%) and air (48,22.9%) were identified. The most predominant isolated genus was Aspergillus (47.5%),followed by Rhizopus (14.2%), Mucor (11.7%), and Cladosporium (9.2%). Aspergillus(39.5%), Cladosporium (16.6%), as well as Penicillium and Sterile hyphae (10.4% each), were the most isolates from the air samples. Moreover, intensive care units (38.5%) and operating rooms (21.9%) had the highest number of isolated fungal colonies. Out of 256 collected samples from equipment and air, 163 (63.7%) were positive for fungal growth.The rate of fungal contamination in instrument and air samples was 128/213 (60.1%) and 35/43 (81.2%), respectively. Among the isolated species of Aspergillus, A. flavus complex (38/96, 39.6%), A. niger complex (31/96, 32.3%), and A. fumigatus complex (15/96, 15.6%) were the commonest species.Conclusion: According to our findings, in addition to air, equipment and instrument should be considered among the significant sources of fungal contamination in the indoor environment of hospitals. Airborne fungi, Hospital, Indoor air, Equipment, Sources of fungal contamination in the indoor environment of hospitals

Multiplicity and Exchange in the World Trade and Applied Diplomacy Structure Regarding Social Network Analysis

In the Multi-relational networks, the study of concurrent choices or multiplicity, and exchanging the choices is important. In this paper, we reviewed multiplicity and exchange in the literature and tried to study these effects in the world network of trade and diplomacy. In addition to reporting the results of exploiting other researchers’ contributions in the case of trade and diplomacy relations on our data, we proposed our own solution to study and evaluate social structure in the situation that multiplicity and exchange effects are significant. Due to the significant number of concurrent choices and choice exchange, we used appropriate probable block model of multiplicity and exchange. Specifically, we found that there are four clear patterns in the world trade and diplomacy network: Trade affected by diplomatic hosting, Trade affected by diplomatic activity, Diplomacy affected by export and Diplomacy affected by import

A Stochastic Decision Support System for Economic Order Quantity Problem

Improving decisions efficiency is one of the major concerns of the decision support systems. Specially in the uncertain environment, decision support systems could be implemented efficiently to simplify decision making process. In this paper stochastic economic order quantity (EOQ) problem is investigated in which decision variables and objective function are uncertain in nature and optimum probability distribution functions of them are calculated through a geometric programming model. Obtained probability distribution functions of the decision variables and the objective function are used as optimum knowledge to design a new probabilistic rule base (PRB) as a decision support system for EOQ model. The developed PRB is a new type of the stochastic rule bases that can be used to infer optimum or near optimum values of the decision variables and the objective function of the EOQ model without solving the geometric programming problem directly. Comparison between the results of the developed PRB and the optimum solutions which is provided in the numerical example illustrates the efficiency of the developed PRB

A Framework for Online Reverse Auction Based on Market Maker Learning with a Risk-Averse Buyer

The online reverse auction is considered as a new e-commerce approach to purchasing and procuring goods and materials in the supply chain. With the rapid and ever-expanding development of information technology as well as the increasing usage of the Internet around the world, the use of an online reverse auction method to provide the required items by organizations has increased. Accordingly, in this paper, a new framework for the online reverse auction process is provided that takes both sides of the procurement process, namely, buyer and seller. The proposed process is a multiattribute semisealed multiround online reverse auction. The main feature of the proposed process is that an online market maker facilitates the seller’s bidding process by the estimation of the buyer’s scoring function. For this purpose, a multilayer perceptron neural network was used to estimate the scoring function. In this case, in addition to hiding the buyer’s scoring function, sellers can improve their bids using the estimated scoring function and a nonlinear multiobjective optimization model. The NSGA II algorithm has been used to solve the seller model. To evaluate the proposed model, the auction process is simulated by considering three scoring functions (additive, multiplicative, and risk-aversion) and two types of open and semisealed auctions. The simulation results show that the efficiency of the proposed model is not significantly different from the open auction, and in addition, unlike the open auction, the buyer information was not disclosed

A monopoly pricing model for diffusion maximization based on heterogeneous nodes and negative network externalities (Case study: A novel product)

Social networks can provide sellers across the world with invaluable information about the structure of possible influences among different members of a network, whether positive or negative, and can be used to maximize diffusion in the network. Here, a novel mathematical monopoly product pricing model is introduced for maximization of market share in noncompetitive environment. In the proposed model, a customer’s decision to buy a product is not only based on the price, quality and need time for the product but also on the positive and negative influences of his/her neighbors. Therefore, customers are considered heterogeneous and a referral bonus is granted to every customer whose neighbors also buy the product. Here, the degree of influence is directly related to the intensity of the customers’ relationships. Finally, using the proposed model for a real case study, the optimal policy for product sales that is the ratio of product sale price in comparison with its cost and also the optimal amounts of referral bonus per customer is achieved