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The social arrangement of organizations determines the potential possibilities of all group of agents in several economic and Operations Research (OR) situations. In this paper, a class of cooperative games in which agents with potential individual possibilities are connected via a hierarchy within an organization is studied. The leader, the agent, and any intermediate agents in the specified hierarchy constitute an important group refering to a peer group and form peer group situations. We consider uncertanty in payoffs in peer group situations. In the sequel peer group settings with fuzzy uncertainty are proposed. Further the associated games are modeled and some game-theoretical solution concepts are provided Futhermore, an application related with an auction situation is given. Finally, we conclude with some remarks and future work. [ABSTRACT FROM AUTHOR]

The United Nations Humanitarian Response Depot (UNHRD) coordinated 515 different shipments (2,420,258 km in total) from six UNHRD depots to 88 different countries to provide a 27,343 m3 volume of products in 2018. The main purpose of the proposed study is to investigate the current distribution plan and identify the potential improvements using operations research techniques. Maximization of the number of covered people, minimization of the traveled distance, and also analyzing the necessity of the response depots are the problems that need to be addressed for UNHRD. Several methods are applied to the UNHRD network for the first time in the literature, and it is aimed to provide a practical solution considering reductions in total distance, time, and cost. To achieve this, three different location-allocation models are devised and deployed on the real UNHRD distribution network, including maximum coverage, P-median, and set covering. As a result of utilizing the P-median model, the total traveled distance is reduced by 58%, and the most significant depots are identified as Accra and Dubai under various distance limitations using the maximum coverage and set covering models. When it comes to the application and managerial implications of the proposed study, the biggest part of demand was supplied by the Dubai depot before the P-median application, and the Accra depot now has the biggest part. Therefore, it is required to increase the volume of the Accra depot. In addition, Accra Depot is preferred 28 times according to the maximum covered model application, with 6 different coverage limits. From this point of view, it is necessary to have efficient and effective planning for the Accra depot in particular. With the set covering method, it is demonstrated the minimum and maximum ranges to serve demand points with the number of the opened depot(s). The most important contribution of the paper to the literature is to address and improve a real humanitarian aid logistics problem using well-known location-allocation models. The study provides a better understanding of the system to have advanced managerial insight by considering the UNHRD logistic network. [ABSTRACT FROM AUTHOR]

Human resources (HR) have a key impact on the creation and implementation of modern products, solutions and concepts. Relatively new and rarely undertaken research challenge in enterprise is optimization of HR in the context of their location and requirements for working conditions. A great challenge here is the transparency and reliability of the collected data. In the article, we present a modern approach to knowledge extraction based on Artificial Intelligence (AI) and Multivariate Adaptive Regression Splines optimizing the availability of HR with a high innovation rate, taking into account their availability time and location. This study was conducted on a group of 5095 young people from the Z generation. A total of 11 variables were analyzed in the context of innovation and presented in this article. The effect of research using machine learning methods is the analysis of the characteristics of generation Z representatives, whose desire is to work in innovative companies. Research results indicate that some regions offer candidates with a higher level and commitment to innovation, and thus make HR more available for the development of innovative products. Chosen models designed by using AI and Operational Research Analytics were presented in the graphic visualization, which is a novelty in the presentation of similar issues in relation to HR. [ABSTRACT FROM AUTHOR]

Rumours are a kind of information that has a impact on social life and economies, which spread quickly and widely, especially, via internet. Recently, the spread of information affects our daily lives due to the increasing number of social media users. Rumours are defined in social areas which are delivered by gossips, fake news, marketing, social media all the way even to revolutions. In this paper, we study the dynamics of a rumour propagation model with a numerical approach. By using an algorithmic technique with an error analysis, the validity of the numerical technique is described. We investigate the model with this numerical approach to explain the dynamics of rumour propagation. Besides, we explain sensitivity analyses of the model of parameters. Then by numerical simulations efficiency of the technique is shown. Finally, the results are displayed and discussed with the help of figures and tables. The paper ends with a conclusion and an outlook to future studies. [ABSTRACT FROM AUTHOR]

The special issue: "Numerical Techniques Meet with OR" of the Foundations of Computing and Decision Sciences consists of two parts which are of the main theme of numerical techniques and their applications in multi-disciplinary areas. The first part of this special issue was already collected in the FCDS Vol. 46, issue 1. In this second part of our special issue editorial, a description of the special issue presents numerical methods which can be used as alternative techniques for Scientific Computing and led Operational Research applications in many fields for further investigation. [ABSTRACT FROM AUTHOR]

Recent techniques such as optogenetics, in vitro and in vivo multielectrode recording, neuro- and brain imaging produce high-quality data that can be used to facilitate the fundamental mechanisms of information processing in our neural domains. As Guest Editors, we will be glad if the selected topics could offer a good coverage of international research dealing with the emerging and complex problems of neuroscience and its associated fields in medicine using OR. I Neuroscience i is a multidisciplinary science concerned with the study of the structure and function of the nervous system. [Extracted from the article]

Neuroscience is a multidisciplinary science concerned with the study of the structure and function of the nervous system. New techniques such as optogenetics, in vitro and in vivo multi-electrode recording, neuroimaging and brain imaging, produce high-quality data that can be used to elucidate the fundamental mechanisms of information processing in the nervous system. This second special issue covers a broad range of topics, advancing the field of neuroscience as well as operations research. [Extracted from the article]

The job scheduling problem is a notoriously difficult problem in combinatorial optimization and Operational Research. In this study, we handle the job scheduling problem by using a cooperative game theoretical approach. In the sequel, sequencing situations arising grom grey uncertainty are considered. Cooperative grey game theory is applied to analyze these situations. Further, grey sequencing games are constructed and grey equal gain splitting (GEGS) rule is introduced. It is shown that cooperative grey games are convex. An application is given based on Priority Based Scheduling Algorithm. The paper ends with a conclusion. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1007/s10479-021-04486-2.Correction to: Annals of Operations Research https://doi.org/10.1007/s10479-021-04486-2This erratum published as several formatting issues were noticed with Tables and equations.Original article has been corrected.Publisher's NoteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.By Erfan Babaee Tirkolaee; Alireza Goli; Selma Gütmen; Gerhard-Wilhelm Weber and Katarzyna SzwedzkaReported by Author; Author; Author; Author; Author [Extracted from the article]

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In this paper, we survey the recent advances and mathematical foundations of gene-environment networks. We explain their interdisciplinary implications with special regard to human and life sciences as well as financial sciences. Special attention is paid to applications in Operational Research and environmental protection. Originally developed in the context of modeling and prediction of gene-expression patterns, gene-environment networks have proved to provide a conceptual framework for the modeling of dynamical systems with respect to errors and uncertainty as well as the influence of certain environmental items. Given the noise-prone measurement data we extract nonlinear differential equations to describe and analyze the interactions and regulating effects between the data items of interest and the environmental items. In particular, these equations reflect data uncertainty by the use of interval arithmetics and comprise unknown parameters resulting in a wide variety of the model. For an identification of these parameters Chebychev approximation and generalized semi-infinite optimization are applied. In addition, the time-discrete counterparts of the nonlinear equations are introduced and their parametrical stability is investigated by a combinatorial algorithm which detects the region of parameter stability. Finally, we analyze the topological landscape of the gene-environment networks in terms of structural stability. We conclude with an application of our analysis and introduce the eco-finance networks. [ABSTRACT FROM AUTHOR]

This paper addresses a study on the transportation problem based on dual-hesitant fuzzy environment. The dual-hesitant fuzzy set accommodates imprecise, uncertain or incomplete information and knowledge situations in real-life operational research problems that are not possible or difficult to tackle by existing fuzzy uncertainties. Here, we present the concept of uncertainty in a transportation problem using dual-hesitant fuzzy numbers. In most of the research works, fuzzy uncertainty has been considered in transportation parameters. However, we consider the dual-hesitant fuzzy numbers to formulate a mathematical model by considering the capacity of delivering the goods by a decision maker. A special emphasis of this paper is to derive an optimal solution of transportation problem with some restrictions under uncertainty by the traditional approach (cf. Vogel's approximation method—VAM) without using any mathematical aids. In this regard, an algorithm is developed to find the optimal solution for the dual-hesitant fuzzy transportation problem including some restrictions. Thereafter, the proposed method is illustrated by giving a numerical example for showing the effectiveness. Finally, conclusions are given with the lines of future studies based on this paper. [ABSTRACT FROM AUTHOR]