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Organization in Finance Prepared by Stochastic Differential Equations with Additive and Nonlinear Models and Continuous Optimization
A central element in organization of financal means by a person, a company or societal group consists in the constitution, analysis and optimization of portfolios. This requests the time-depending modeling of processes. Likewise many processes in nature, technology and economy, financial processes suffer from stochastic fluctuations. Therefore, we consider stochastic differential equations (Kloeden, Platen and Schurz, 1994) since in reality, especially, in the financial sector, many processes are affected with noise. As a drawback, these equations are hard to represent by a computer and hard to resolve. In our paper, we express them in simplified manner of approximation by both a discretization and additive models based on splines. Our parameter estimation refers to the linearly involved spline coefficients as prepared in (Taylan and Weber, 2007) and the partially nonlinearly involved probabilistic parameters. We construct a penalized residual sum of square for this model and face occuring nonlinearities by Gauss-Newton's and Levenberg-Marquardt's method on determining the iteration step. We also investigate when the related minimization program can be written as a Tikhonov regularization problem (sometimes called ridge regression), and we treat it using continuous optimization techniques. In particular, we prepare access to the elegant framework of conic quadratic programming. These convex optimation problems are very well-structured, herewith resembling linear programs and, hence, permitting the use of interior point methods (Nesterov and Nemirovskii, 1993).

Intro -- Preface -- Organization -- Contents -- Computational Intelligence in Social Sciences -- Social Disintegration Index and Its Applications -- Abstract -- 1 Introduction -- 2 Social Disintegration Index -- 3 Suicides as Disintegration -- 4 Mentalities and Behavior -- 5 Discussion -- 6 Conclusion -- References -- Optimization of Data Processing and Presentation in Social Surveys: From Likert-Means to "Yes Percentage" -- Abstract -- 1 Introduction: Theoretical and Practical Context of the Study -- 2 Methods -- 3 Results -- 4 Conclusion and Discussion -- References -- Modeling and Analysis of Social-Behavioral Processes -- Modeling and Simulation of Impact and Control in Social Networks -- Abstract -- 1 Introduction -- 2 Analysis and Prediction Problems -- 3 Optimization and Game Theoretic Control Problems -- 4 Conclusions -- References -- Finding Fake News Key Spreaders in Complex Social Networks by Using Bi-Level Decomposition Optimization Method -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Data Set -- 3.2 Node-Level Sphere of Influence -- 3.3 Network-Level Analysis -- 4 Experimental Results -- 5 Conclusion and Discussion -- Acknowledgment -- References -- An International Comparative Analysis for Autonomous Vehicles and Their Effects -- Abstract -- 1 Introduction -- 2 Outline of the Surveys -- 3 Comparative Results of Consciousness -- 4 Effects of Autonomous Vehicles -- 5 Conclusions -- Acknowledgment -- References -- An Investigation of Social-Behavioral Phenomena in the Peer-Review Processes of Scientific Foundations -- Abstract -- 1 Introduction -- 2 Professional Examination and Decision-Making in the Appraisal of Research Projects: Model Assumptions -- 3 Mechanisms for the Rating of Scientific Projects by Researchers, Realization of Feedback, and Conceptual Model Scheme.

This book presents the latest developments in optimization and optimal control models; exact, approximate and hybrid methods; and their applications in lean and green supply chains. It examines supply chain network design and modeling, closed loop supply chains, and lean, green, resilient and agile or responsive networks, and also discusses corporate social responsibility and occupational health and safety. It particularly focuses on supply chain management under uncertainty - employing stochastic or nonlinear modeling, simulation based studies and optimization - multi-criteria decision-making and applications of fuzzy set theory, and covers various aspects of supply chain management such as risk management, supplier selection or the design of automated warehouses. Lastly, using experimental applications and practical case studies, it shows the impact of lean and green applications on vehicle/fleet management and operations management.

EN The analysis of labour market participation of the working-age population is a complex issue due to the multitude of factors determining this phenomenon, e.g. age, material status, availability of labour market offers to meet individual employee's needs. People with disabilities are undoubtedly among those most at risk of social exclusion, which is clearly indicated and underlined by the issues addressed in this article. The current economic situation in Poland makes it possible for people with disabilities to undertake professional activity, especially in so-called sheltered employment conditions - in sheltered workshops, as well as in open employment conditions - in commercial enterprises. The results of research presented in this article are intended to present the economic situation of people with disabilities in Poland in comparison with other EU countries. Based on the results of own research, carried out in cooperation with a non-profit organisation - one of the most recognisable student associations in Poland - and on statistics from individual EU countries collected by government institutions, a model was created to forecast the demand for jobs in both market environments. The need of people with disabilities both to integrate with non-disabled people and their reluctance to work in closed environments of people with disabilities and the resulting social conditions were recognized.

Electric energy plays an irreplaceable role in nearly every person's life on earth; it has become an important subject in operational research. Day by day, electrical load demand grows rapidly with increasing population and developing technology such as smart grids, electric cars, and renewable energy production. Governments in deregulated economies make investments and operating plans of electric utilities according to mid- and long-term load forecasting results. For governments, load forecasting is a vitally important process including sales, marketing, planning, and manufacturing divisions of every industry. In this paper, we suggest three models based on multivariate adaptive regression splines (MARS), artificial neural network (ANN) and linear regression (LR) methods to model electrical load overall in the Turkish electricity distribution network, and this not only by long-term but also mid- and short-term load forecasting. These models predict the relationship between load demand and several environmental variables: wind, humidity, load-of-day type of the year (holiday, summer, week day, etc.) and temperature data. By comparison of these models, we show that MARS model gives more accurate and stable results than ANN and LR models.

Electric energy plays an irreplaceable role in nearly every person's life on earth; it has become an important subject in operational research. Day by day, electrical load demand grows rapidly with increasing population and developing technology such as smart grids, electric cars, and renewable energy production. Governments in deregulated economies make investments and operating plans of electric utilities according to mid- and long-term load forecasting results. For governments, load forecasting is a vitally important process including sales, marketing, planning, and manufacturing divisions of every industry. In this paper, we suggest three models based on multivariate adaptive regression splines (MARS), artificial neural network (ANN) and linear regression (LR) methods to model electrical load overall in the Turkish electricity distribution network, and this not only by long-term but also mid- and short-term load forecasting. These models predict the relationship between load demand and several environmental variables: wind, humidity, load-of-day type of the year (holiday, summer, week day, etc.) and temperature data. By comparison of these models, we show that MARS model gives more accurate and stable results than ANN and LR models.

Abstract
Background: This paper generalizes the results of Embedding problem of Fuzzy Number Space and its extension into a Fuzzy Banach Space C(Ω) × C(Ω), where C(Ω) is the set of all real-valued continuous functions on an open set Ω.
Objectives: The main idea behind our approach consists of taking advantage of interplays between fuzzy normed spaces and normed spaces in a way to get an equivalent stochastic program. This helps avoiding pitfalls due to severe oversimplification of the reality.
Method: The embedding theorem shows that the set of all fuzzy numbers can be embedded into a Fuzzy Banach space. Inspired by this embedding theorem, we propose a solution concept of fuzzy optimization problem which is obtained by applying the embedding function to the original fuzzy optimization problem.
Results: The proposed method is used to extend the classical Mean-Variance portfolio selection model into Mean Variance-Skewness model in fuzzy environment under the criteria on short and long term returns, liquidity and dividends.
Conclusion: A fuzzy optimization problem can be transformed into a multiobjective optimization problem which can be solved by using interactive fuzzy decision making procedure. Investor preferences determine the optimal multiobjective solution according to alternative scenarios.

"This book highlights the latest research innovations and applications of algorithms designed for optimization applications within the fields of engineering, IT, and economics, focusing on a variety of methods and systems as well as practical examples"--

A game is a situation which conceives and concludes through reality involving a set of players, may be two or more. Conclusions of such situations are not always very easy, e.g., if one wins other loses. Sometimes, when considering the totality, the outcome of game is not linguistically zero, and we utter the term non-zero-sum game. Prisoners' dilemma game is one of most cited examples in non-zero-sum game literature. In this paper, human trafficking, one of the most rising problems of today's society is viewed through Prisoners' dilemma game using hesitant interval-valued intuitionistic fuzzy-linguistic term set, where linguistic terms in interval are expressed by linguistic semantics first, and then corresponding indices are used. Finally, Nash equilibrium is derived from the given definition, and the achieved result establishes a close contact with reality using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Dominance property of matrix game theory.

In recent years, the relationship between companies and suppliers has changed with the continuous rise in environmental awareness and customer expectations. In order to fulfill customers' needs, the actors in a Supply Chain (SC) network sometimes compete and sometimes cooperate with each other. In SC management, both competitive and collaborative strategies have become important and have required different points of view. In a collaborative environment, companies should strive for common targets with mutual relationship. After managers decided to share their resources, some positive effects have appeared on the companies and suppliers' performance such as profitability, flexibility and efficiency. Consequently, many companies are willing to cooperate with each other in a SC network because of these reasons. On the other hand, Closed-Loop Supply Chain (CLSC) management has been attracting a growing interest because of increased environmental issues, government regulations and customer pressures. Based on this initiative, our paper presents a novel allied CLSC network design model with two different SCs including common suppliers and common collection centers. First, a decentralized multi-level Mixed-Integer Linear Programming (MILP) model that consists of two different levels of Decision Makers (DMs) is developed. The plants of common SCs comprise the upper-level DMs, common suppliers, common collection centers, and the logistics firm comprises the lower-level DMs. A novel Interactive Fuzzy Programming (IFP) approach using Fuzzy Analytic Hierarchy Process (AHP) is proposed to obtain a preferred compromise solution for the developed model. Through use of Fuzzy AHP in the proposed IFP approach, the DMs can identify the importance of the lower-level DMs. In order to validate the developed model and the proposed IFP approach, a numerical example is implemented. According to the obtained results, our proposed IFP method outperforms Sakawa and Nishizaki's(1) and Calik et al.' s(2) approach with respect to the satisfaction degrees of upper-level DMs for the developed CLSC model.