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The study aims to optimize truck routes by minimizing social and economic costs. It introduces a strategy involving diverse drones and their potential for reusing at DNs based on flight range. In HTDRP-DC, trucks can select and transport various drones to LDs to reduce deprivation time. This study estimates the nonlinear deprivation cost function using a linear two-piece-wise function, leading to MILP formulations. A heuristic-based Benders Decomposition approach is implemented to address medium and large instances. Valid inequalities and a heuristic method enhance convergence boundaries, ensuring an efficient solution methodology.

Research has yet to address critical factors in disaster logistics: minimizing the social and economic costs simultaneously and using drones in relief distribution; deprivation as a social cost measures the human suffering from a shortage of relief supplies. The proposed hybrid truck-drone routing problem minimizing deprivation cost (HTDRP-DC) involves distributing relief supplies to dispersed demand nodes with undamaged (LDs) or damaged (DNs) access roads, utilizing multiple trucks and diverse drones. A Benders Decomposition approach is enhanced by accelerating techniques.

Incorporating deprivation and economic costs results in selecting optimal routes, effectively reducing the time required to assist affected areas. Additionally, employing various drone types and their reuse in damaged nodes reduces deprivation time and associated deprivation costs. The study employs valid inequalities and the heuristic method to solve the master problem, substantially reducing computational time and iterations compared to GAMS and classical Benders Decomposition Algorithm. The proposed heuristic-based Benders Decomposition approach is applied to a disaster in Tehran, demonstrating efficient solutions for the HTDRP-DC regarding computational time and convergence rate.

Current research introduces an HTDRP-DC problem that addresses minimizing deprivation costs considering the vehicle’s arrival time as the deprivation time, offering a unique solution to optimize route selection in relief distribution. Furthermore, integrating heuristic methods and valid inequalities into the Benders Decomposition approach enhances its effectiveness in solving complex routing challenges in disaster scenarios.

The purpose of this paper is to introduce a model of redistribution of point radiation defects, interaction between themselves and redistribution of their simplest complexes in a multilayer structure. The model gives a possibility to qualitatively describe nonmonotonicity of distributions of concentrations of radiation defects on interfaces between layers of the structure, which recently was found experimentally. To take into account the nonmonotonicity, the authors complement the model for the analysis of distribution of concentration of radiation defects, which were recently used in the literature. To analyze the model, the authors used an approach of solution of boundary problems, which could be used without crosslinking of solutions on interfaces between layers of the considered multilayer structures.

The authors introduce a model of redistribution of point radiation defects, interaction between themselves and redistribution of their simplest complexes in a multilayer structure. The model gives a possibility to qualitatively describe nonmonotonicity of distributions of concentrations of radiation defects on interfaces between layers of the structure, which recently was found experimentally. To take into account the nonmonotonicity, the authors complement the model for analysis of distribution of concentration of radiation defects, which were recently used in the literature. To analyze the model, the authors used an approach of solution of boundary problems, which could be used without crosslinking of solutions on interfaces between layers of the considered multilayer structures.

The authors obtain better agreement of obtain results in comparison with recently obtained results in the literature.

The results are original.

The purpose of this paper is to analyze the redistribution of dopant and radiation defects to determine conditions which correspond to decreasing of elements in the considered inverter and at the same time to increase their density.

In this paper, the authors introduce an approach to increase integration rate of elements in a three-level inverter. The approach is based on decrease in the dimension of elements of the inverter (diodes and bipolar transistors) due to manufacturing of these elements by diffusion or ion implantation in a heterostructure with specific configuration and optimization of annealing of dopant and radiation defects.

The authors formulate recommendations to increase density of elements of the inverter with a decrease in their dimensions.

Optimization of manufacturing of integrated circuits and their elements.

The results of this paper are based on original analysis of transport of dopant with account transport and interaction of radiation defects.

The purpose of this paper is to analytically model redistribution of dopant in a heterostructure during annealing of dopant and/or radiation defects (during the modeling, the authors consider two types of infusing of the dopant: dopant diffusion and ion implantation). The authors consider a heterostructure, which consists of a substrate and an epitaxial layer. After that the authors consider doping of several specific areas to manufacture heterodiodes and heterobipolar transistors framework hybrid cascaded multilevel inverter.

Based on the modeling, the authors introduce an approach to increase density of diodes and bipolar transistors framework hybrid cascaded multilevel inverter, which has been manufactured based on the heterostructure. The approach is based on using inhomogeneity of the heterostructure and optimization of annealing of dopant and/or radiation defects.

The approach gives us possibility to take into account nonlinearity of considered processes.

The authors introduce an analytical approach to model diffusion and ion types of doping with account concurrent changing of parameters in space and time.

The purpose of this study is to develop a holistic optimization model for an integrated sustainable fleet planning and closed-loop supply chain (CLSC) network design problem under uncertainty.

A novel mixed-integer programming model that is able to consider interactions between vehicle fleet planning and CLSC network design problems is first developed. Uncertainties of the product demand and return fractions of the end-of-life products are handled by a chance-constrained stochastic program. Several Pareto optimal solutions are generated for the conflicting sustainability objectives via compromise and fuzzy goal programming (FGP) approaches.

The proposed model is tested on a real-life lead/acid battery recovery system. By using the proposed model, sustainable fleet plans that provide a smaller fleet size, fewer empty vehicle repositions, minimal CO₂ emissions, maximal vehicle safety ratings and minimal injury/illness incidence rate of transport accidents are generated. Furthermore, an environmentally and socially conscious CLSC network with maximal job creation in the less developed regions, minimal lost days resulting from the work's damages during manufacturing/recycling operations and maximal collection/recovery of end-of-life products is also designed.

Unlike the classical network design models, vehicle fleet planning decisions such as fleet sizing/composition, fleet assignment, vehicle inventory control, empty repositioning, etc. are also considered while designing a sustainable CLSC network. In addition to sustainability indicators in the network design, sustainability factors in fleet management are also handled. To the best of the authors' knowledge, there is no similar paper in the literature that proposes such a holistic optimization model for integrated sustainable fleet planning and CLSC network design.

The purpose of this paper is to design and construct a low‐cost current‐voltage tester, bearing in mind the short falls of the existing testers and the ever‐increasing price of the testers currently on the market. The I‐V tracer presented in this paper uses a variable external power supply unit (PSU) as the load, in order to obtain the entire operating range of a PV module from open circuit through maximum power to short circuit condition.

The I‐V tracer presented in this paper was divided into three main sections, mainly the data acquisition system (DAS), which comprises an A/D computer card, temperature card, electromechanical relays, current and voltage transducers, aluminum housed resistors and power MOSFETS, the variable load (programmable variable PSU) and finally the signal processing unit. These components were integrated and finally interfaced to a PC.

The results obtained using this system compared with the capacitive tester show a low percentage difference of <1 from the comparative I‐V curves measured. The results measured by the PSU tester are also of high accuracy. The findings also demonstrated the fact that most of the components found in most university laboratories can be used to build the PSU tester and still obtain highly accurate results.

Since some components are semiconductors, which have a limited lifetime, they need to be changed if they fail. Mostly the MOSFETS should be replaced when no switching signal is sent.

This low‐cost PSU tester is suitable for researchers in disadvantaged institutions whose research capabilities are limited due to the high cost of this equipment.

The PSU tester uses a variable power supply as the load to measure PV module I‐V curves. The system is capable of measuring up to eight modules at the same time, making it possible to analyze PV modules within the same time frame.

The healthcare system is regarded as one of the most critical service industries. The surgical unit is the heart of hospitals in that any failures directly affect the safety of patients, so they should be managed thoroughly. It is an intricate multi-attributes decision-making problem with uncertainty. Uncertain information in the form of fuzzy sets theory has been applied widely to describe the different aspects of system uncertainty. This study aims to present a new methodology to manage the healthcare system failures due to the multi-attributes decision-making process.

This study introduces a new risk evaluation methodology by failure mode and effect analysis (FMEA) and MULTIMOORA method. Group decision-making process in this methodology is presented under uncertain information in the form of interval-valued hesitant fuzzy linguistic sets (IVHFLSs). IVHFLSs encompass both qualitative and quantitative interpretation of experts to reflect their preferences, as well the ability and flexibility of derivation of linguistic information by several linguistic terms increase. To avoid the different ranking order of MULTIMOORA approaches, a new interval multi-approaches multi-attribute methodology, namely, technique of precise order preference (TPOP), is extended to provide precise ranking order.

The application and precision of proposed integrated IVHFL-MULTIMOORA methodology with TPOP is examined in a case study of healthcare systems. The results indicate the superiority of proposed methodology to prioritize and assess the failures as well as handling system uncertainty.

This study addresses the challenges of an organization to prioritize potential failures by implementing FMEA method. Moreover, this paper contributes to making the manager's ability in decision-making. The value of this study can be discussed in two aspects. First and foremost, this study provides a new FMEA-based methodology to rank failures precisely. The results prove that the proposed methodology is more robust to changes of different ranking order methods, applied by FMEA. On the other hand, using the capability of IVHFLSs allows collecting accurate information in an ambiguous and uncertain environment.

In general, regular selection tools for reference materials do not provide adequate coverage for government documents and technical reports. The situation is improving in the case of government documents in recent times as the awareness of the importance of documents is growing. For example, Reference Services Review publishes surveys and special features on government documents. Libraries Unlimited publishes a biennial guide titled, Government Reference Books. In contrast, very little attention is paid to the technical reports literature and they remain unexploited by the average reference librarian.

Properly conceived, conducted and interpreted, motivation research can be an extremely powerful management tool, designed to help the manufacturer or advertiser to sell more goods. Its aim is to expose the market situation, explain it and suggest courses of action which will lead to desired changes. It is a way of looking at a problem rather than a collection of specialist techniques and is strictly practical. Hence it can be used alongside other market research tools for the solution of marketing problems and can be applied to a wide range of business activities. Much of its development has been in the advertising field but it can also help in the formulation of production policy, solving packaging problems and marketing operations. It is examined here in all these contexts. The idea of motivation research, the reasons for its use and the techniques by which to apply it are discussed, as well as the pitfalls that are likely to occur. New and imaginary case studies are used throughout to illustrate points. A review of the subject literature is included.