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This research presents a novel integrated mathematical programming model for green healthcare supply network design. A multi-graph integrated supply network was designed to meet real-world situations. Minimizing total cost and minimizing delivery time are considered as the objective functions. Since the considered problem is np-hard and the presented mathematical model is very complex and highly constrained, an innovative non-dominated ranked genetic algorithm (NRGA) called M-NRGA is developed to solve the real word problems. Three different selection procedures were implemented to improve the quality and diversity of solutions in the Pareto-front resulted from M-NRGA. Several numerical examples and a case study are solved to validate the model and performance evaluation of the solution algorithm. Four different performance metrics are implemented for performance evaluation of the solution algorithm. The quality of resulted solutions, the diversity of the solutions in the Pareto front are calculated for evaluation. The results are compared with two other meta-heuristic algorithms.

Optimizing the perishable food, supply chain, taking into account all aspects, such as location, time, inventory control and routing, has become one of the top research priorities in today's competitive market. The primary objective is to reduce the overallcost, and the second one is to diminish the probability of warehouses failing to maintain the product (storage waste), which in turn, maximizes product quality.In this research, the issue of integrated supply chainplanning has been investigated in which it is assumed that there is a central warehouse for food distribution. The model developed in the present study considers two contradictory objectives for supply chainoptimization.In this research, foods are classified into three categories with the rate of deterioration common, high and very high. The concept of Pareto boundary and a set of optimal responses have been used. Demand is defined as uncertain and dependent on two factors, the demand for the prior period and the remaining time until the expiration of the products. The research problem is solved with both NSGA-II and NRGA algorithms whose parameters of these two algorithms are optimized by the Taguchi method. The two efficient boundaries are created by the four criteria MID, DM, SM and NOS. Finally, concluded that the efficiency of the NSGA-II method in solving the research problem and forming an effective boundary is higher than the NRGA method.

The final agreement on the timing of project completion is one of the obvious problems between project managers and their clients. There have been numerous reports of customers requesting shorter completion times than previously announced. This request will definitely affect the three project factors of overall cost, final quality of the project, and risk of implementation. This paper proposes a multipurpose cumulative complex linear programming to minimize "project overhead," "increase projects total risk" and "increase overall project quality" due to “time constraints." In other words, the proposed study is fully implemented among the four goals mentioned to shorten the project duration. Computational experiments have also been used to evaluate the performance of the proposed model. The main objective of this paper is to optimize the integration of the four factors of the survival pyramid (time, cost, quality, and risk) in industrial projects simultaneously under uncertainty. An innovative solution based on the multi-objective genetic algorithm (NSGA-II) is presented. This model is then used to solve a problem in another study and its results, strengths, and weaknesses compared to the previous model are evaluated. The results show the performance of the proposed model in all four factors is better than the previous models.

This research paper looks into Game Theory while immensely addressing the historical background of this theory. The document also gives an overview and definition of relevant terminologies related to this theory like a game, Nash equilibrium, and dominance which form the basis of the theory concept. It also focuses on mixed strategies, extensive games with both perfect and imperfect information, auction bidding, and their relevant practical application of the concept as applied in the field of economics.

Background: Thyroid cancer has been growing rapidly during the last decades. Radioiodine-131 (I-131) as an appropriate therapy modality is currently using in the treatment of cancer and hyperthyroidism diseases. This radiotracer is considered as a cause of oxidative DNA damage in nontarget cells and tissues. The aim of this study was to investigate the effects of curcumin and trehalose on the level of DNA double-strand breaks (DSBs) caused by I-131 in human lymphocytes. Materials and Methods: First, 6-mL blood samples were taken from each of the five volunteers. After 1 h of preincubation with the antioxidants, a total of 20 μCi I-131/2 mL (blood + NaCl) was added to each sample, and then, the samples were reincubated for 1 h. Lymphocytes were separated and the mean DSB levels were measured for each sample through γ-H2AX assay to evaluate the effects of antioxidants. Results: After 1-h incubation with I-131, the DSBs increased by 102.9% compared to the control group (0.343 vs. 0.169 DSB/cell; P = 0.00). Furthermore, compared to the control + I-131 group, curcumin and trehalose reduced the DSBs by 42% and 38%, respectively. There was a significant decrement (P = 0.00) in the levels of DSBs of the curcumin + I-131 and trehalose + I-131 subgroups compared to the control + I-131 subgroup. Furthermore, there was no significant relationship between the radioprotective effect of curcumin and trehalose (P = 0.95). Conclusion: The use of curcumin and trehalose as antioxidant can reduce the numbers of DSBs caused by I-131. Meanwhile, the radioprotective effect of curcumin was more than trehalose.

The impressive role in the proper design of facility layout on productivity cannot be simply overlooked. So far, many models of the genetic algorithm have been introduced to solve such problems. The common approach of all these methods is to eliminate unacceptable answers. But given that unacceptable responses also have positive characteristics that can have a positive effect on next-generation fitness, this positive character can be exploited. In the multi-objective and multi-scale model presented, graded punishment is intended for such solutions, but will benefit from their positive features. Finally, the effectiveness of this method was evaluated by studying a case study. The results confirm the model's ability to improve the existing conditions. The main application of this model, in multi-layered organizations, is the allocation of several facilities to one location, depending on its capacity. It is also used to design workshop facility layouts.

Nowadays, business competition turns from inter-company competition into competition between supply networks (Rice and Hoppe, 2001) [1] . Winning customer satisfaction is one of the primary elements of survival in the market. Organizations are no longer committed to long-term cooperation with suppliers. Furthermore, choosing suppliers is only based on their qualifications with regard to providing service and their compatibility with the type of customers’ demands. Thus, each supply network needs to be designed according to a specific market opportunity with regard to structure and members. As a result, the structure of supply networks must be more flexible and move toward dynamics (Humphries and Mena, 2012) [2] . Delivery time is one of the main criteria for evaluating the performance of a supply network. Delivery speed and accuracy in dynamic supply networks are the main challenges ahead of network managers due to the short-time nature of such networks (da Silveira and Arkader, 2007) [3] . Therefore, from a different viewpoint, uncertainty and its sources, which directly affect delivery time, could not be ignored easily. Therefore, this study essentially focuses on the impact of uncertainty on delivery time in three nodes supply networks. The aim of this paper is to identify the impact of the accumulation of the individual delivery time uncertainties on overall delivery time uncertainty. The idea is the type of network and their structures have a crucial impact on the delivery time uncertainty. To prove this idea a probabilistic method is created to measure and evaluate this influence by implementing the Markov theorem. This research is an important step toward the better understanding of more complex networks and the impact of network type in the delivery time uncertainty of these networks.

Today, business models are invariably part of complex networks of suppliers, manufacturers and distributors. Uncertainty is recognized as an inevitable characteristic of supply networks and managers need to be aware of its specifications and consequences of that. Therefore, understanding, acknowledgment, and moderation of the causes and effect of uncertainty is crucial. Under-controlled uncertainty leads to the improvement of networks’ performances and reliable networks. This paper complies with uncertain complex supply networks with their fundamental types. By defining critical routes in PERT networks, a combination of stochastic and mathematical models calculates the delivery time uncertainty in supply networks. This approach can be used as a tool for managers to control and monitor uncertainty in complex networks.

In this paper, a multiple objective programming model has been presented as a supply chain with the general purpose of adopting an integrated approach such that with making optimal decisions about the optimum allocation of limited sources in the supply chain, selection of the suppliers, production, distribution and supply programming yields, the least cost and the most income and finally maximizes the profit of the chain. The proposed model attempts to regard the integration condition very well with consideration of factors such as the conditions for suppliers, producers, and distributors as well as free relations of producers with each other in the direction of providing products through a process or even the products from each other. The presented model, for more adaptation to reality, is flexible against the dynamism of the demand, and it considers the effect of economic factors on decisions such as inflation. A numerical example is then given to show the applicability of the proposed model. This model covers the operational dimension of the chain very well with appropriate programming for production and controlling the inventories.

Logistics is an essential part of business and supply chains. It connects continents, enterprises and commerce on different levels. Resources in logistics are a core factor on all levels and have been under research in many disciplines and sciences. Multidisciplinary nature of logistics has highlighted the unforeseen and overlooked resources in individual constituents of intricate logistic processes. Understanding and addressing them as resources by themselves is an important step towards increasing efficiency of logistics processes. This paper is a collective effort of different research approaches and methodologies applied in logistics to share knowledge via a multidisciplinary view on efficient use and management of resources.

In this paper, electrochemical polymerization of N-phenylglycine (PG), by using glassy carbon (GC) electrode as working electrode, in 0.2 M HClO4/NaClO4 aqueous solution has been introduced. Cyclic voltammetry (CV) was used for synthesis of the poly (N-phenylglycine) (PPG). Also electrochemical behavior of synthesized polymer was investigated by CV. To obtain the best conditions for electropolymerization method, different factors such as scan rate, potential range, type of doping agents, concentrations of monomer and doping agents were optimized. Polymerization of PG has been confirmed by UV-Vis and FTIR spectroscopy. The morphology of PPG film was introduced by scanning electron microscopy (SEM).

Although information and communication technology (ICT) has been playing an important role in the development of business and society for more than thirty years, its potential benefits and risks for the environment are still not sufficiently explored. This is mainly because of the complex interdependencies between ICT and different other areas of business and society that together build a very complex ecosystem. In this paper, we present a holistic approach that treats ICT as a part of the global ecosystem. This approach combines datacentric methods that are typically used to analyze communication networks with widely applicable thermodynamic tools. The proposed approach is well suited to investigate complex heterogeneous systems and assess their environmental sustainability. In particular, we briefly present and discuss the application of such an approach on an exemplary model of cloud computing use in Austria.

Currently, the total energy consumption of the information and communication technology (ICT) sector is continuously increasing due to the fast penetration of ICT into many areas of business and society. Particularly high growth rates have been observed in the area of technologies and applications for communication networks. Over the last decade, there has been an exponential increase of both data traffic and number of devices connected to the Internet, which has led to a fast increase of network capacity. In this context, the role of the network infrastructure is becoming increasingly important because satisfying the need for high capacity generally means higher energy consumption of the network equipment. Especially mobile networks have experienced constant evolutions that have led to new technology generations and advanced radio interfaces capable of providing data rates in the order of hundreds of Mbps or even Gbps. Additionally, the number of active mobile subscribers has grown continually and rapidly. Even through the use phase is very important because of the high energy consumption and related greenhouse emissions of telecom infrastructures, it is just a part of the story. The whole life cycle, i.e., also the production and disposal phases should be considered when determining sustainability of communication networks, especially because of the relatively short life-cycle of ICT devices. In this paper, we report results of a study that apply widely used thermodynamic tools in combination with network modeling to assess sustainability of radio access networks. In particular, we utilize the concept of available energy or exergy to determine the environmental impact of the whole life cycle of radio access network infrastructure and present results of a case study of radio access network for the city of Vienna.