Constrained Optimization with Evolutionary Algorithms: A Comprehensive Review

Global optimization is an essential part of any kind of system. Various algorithms have been proposed that try to imitate the learning and problem solving abilities of the nature up to certain level. The main idea of all nature-inspired algorithms is to generate an interconnected network of individuals, a population. Although most of unconstrained optimization problems can be easily handled with Evolutionary Algorithms (EA), constrained optimization problems (COPs) are very complex. In this paper, a comprehensive literature review will be presented which summarizes the constraint handling techniques for COP

Performance Evaluation of Nature-Inspired Algorithms in constrained Optimization

In almost all scientific contributions to the field of Nature-Inspired Algorithms (NIAs), the researchers select some benchmark test suites, which makes possible to draw conclusions on the merit of the proposed algorithm. Hence, it is a vital task to compose comprehensive test suites with the aim of covering variety of different scenarios. Furthermore, while conducting comparative analysis of results obtained with NIAs, selection of the proper performance indicators are of paramount importance. This paper intends to address these two topics with a special stress on NIAs designed for constrained optimization

Human chromosome classification using competitive support vector machine teams

Classification of chromosome is a challenging task and requires very precise autonomous classifier. This paper proposes to employ competing support vector machines (SVMs) placed in a grid. Each agent in cells of the grid is responsible to distinguish two classes. Overall output is determined by simple majority voting of SVMs. Relying same principle as the work by Palalic and Can [17], we compared the results obtained where the algorithms delivers better accuracy

Bewertung von an der türkischen Terminbörse gehandelten Futureskontrakten

Das Ziel dieser Arbeit ist es, erstens einen Überblick auf die verschiedenen Bewertungsansätze von Futureskontrakten zu geben und dadurch einen Rahmen für die nachfolgende Effizienzüberlegungen der türkischen Terminbörse zu geben.Zweitens soll durch Vergleich der theoretischen Preise verschiedener Arten von Futureskontrakten mit den an der türkischen Terminbörse realisierten Preise analysiert werden, in welchem Ausmaß die realisierten Preise den arbitragefreien "Sollwerte" entsprechen, und wodurch größere Abweichungen zwischen Modellpreis und Marktpreis erklärbar sind.The goal of this diploma thesis is first of all to give an overview of different pricing approach of Futures and thus to give a framework for the efficiency considerations of the Turkish futures exchange. Secondly, it should be analyzed by comparing of the theoretical prices with realized prices of different kinds of futures on the turkish futures exchange, how10

Adapting social media strategies: a comparative analysis of Turkish Airlines, Qatar Airways, and Emirates before, during, and after the COVID-19 Pandemic

In recent years, the aviation industry has transformed significantly, driven by the increasing importance of digital technologies and social media for communication and marketing. The COVID-19 pandemic accelerated this transformation, posing unprecedented challenges to airlines. The present study investigates how Turkish Airlines, Qatar Airways, and Emirates adapted their social media strategies before, during, and after the pandemic. The research has a threefold focus: (i) assessing pre-pandemic social media strategies, (ii) examining strategy evolution during the pandemic, and (iii) comparing the effectiveness of these strategies before and after COVID-19. By exploring how these airlines leveraged social media to navigate pandemic-related disruptions and maintain vital connections with passengers, this study provides valuable insights. These findings hold significant implications for aviation stakeholders, marketing professionals, and researchers, shedding light on the evolving role of social media in crisis communication and marketing. The study uncovered interesting changes in how airlines use Twitter. After the pandemic, they started using more emojis, and their messages shifted from promoting services to expressing hope during the pandemic and back to promotions afterward. They played with visuals and hashtags. Pricing-wise, they offered discounts for students, different ticket options, and bundled services. In promotions, they focused on being environmentally and socially responsible, user convenience, and specific events. They mainly shared updates on flights, achievements, and travel advice. To engage people, they used quizzes, replied directly to customers, and targeted specific groups. For marketing managers, the study suggests being more customer-focused, emphasizing environmental and social responsibility, offering diverse pricing, celebrating milestones, and creating engaging content. Overall, the findings provide practical insights for adjusting marketing strategies in the ever-changing world of airlines, especially considering the challenges brought by COVID-19

A Literature Survey on Association Rule Mining Algorithms

With the development of database technology, the need for data mining arises. As a result, Association Rule Mining(ARM) has become a very hot topic in data mining. This paper presents definition and application areas of association rules. Furthermore, a comprehensive literature review on the existing algorithms of ARM is conducted with a special focus on the performance and application areas of the algorithms. These algorithms are in general classified into three main classes: (1) based on frequent itemset, (2) based on sequential pattern, and (3) based on structured pattern. The algorithms are developed to improve the accuracy and decrease the complexity, and execution time. However, it is hard to say that they do always succeed to optimize all these aspects simultaneously. Hence, there is still some space to develop more efficient algorithms for different data structures

DESIGNING REVERSE LOGISTICS NETWORK FOR END-OF-LIFE VEHICLES: A SUSTAINABILITY PERSPECTIVE IN A FRAGILE SUPPLY CHAIN

Environmental guidelines in the automotive industry greatly emphasize the recycling, remanufacturing, and recovering of end-of-life vehicles (ELVs). Given the principle of extended producer responsibility, developing an effective reverse logistics network is the most significant digit ahead of the industry. However, initial attempts addressing the reverse logistics network design (RLND) problem were short-sighted, focusing on cost minimization. Undoubtedly, the whole concept of recycling was founded on the pillars of sustainability. Accordingly, reverse logistics network design must be motivated by long-term environmental and societal benefits. This fact has become even more prominent in the current pandemic environment as COVID-19 has added serious uncertainties and risks to the supply chain processes. This paper reiterates the essence of sustainability goals and proposes a multi-objective fuzzy mathematical model to RLND problem for ELVs under such a fragile and fuzzy environment. The coverage of the proposed model is to optimally determine the locations and numbers of the facilities and the flows among them concerning environmental, social, and economic aspects. Hence, the model aims to reach a robust compromise solution that leads to a resilient network design. A real case study on the ELV market in Istanbul/Turkey proves the merit of the developed model