Suat Kasap

A novel metaheuristics approach for continuous global optimization

This paper proposes a novel metaheuristics approach to find the global optimum of continuous global optimization problems with box constraints. This approach combines the characteristics of modern metaheuristics such as scatter search (SS), genetic algorithms (GAs), and tabu search (TS) and named as hybrid scatter genetic tabu (HSGT) search. The development of the HSGT search, parameter settings, experimentation, and efficiency of the HSGT search are discussed. The HSGT has been tested against a simulated annealing algorithm, a GA under the name GENOCOP, and a modified version of a hybrid scatter genetic (HSG) search by using 19 well known test functions. Applications to Neural Network training are also examined. From the computational results, the HSGT search proved to be quite effective in identifying the global optimum solution which makes the HSGT search a promising approach to solve the general nonlinear optimization problem.

A Study on Green Manufacturing in a Car Battery Manufacturing Plant

This study presents an environmental manufacturing system analysis for companies looking for the benefits of environmental management in achieving high productivity levels. When the relationship between environmental costs and manufacturing decisions is examined, it can be seen that the productivity of the company can be increased by adopting a methodology of an environmentally integrated manufacturing system analysis. This study presents such a methodology and the roadmap for generating environmentally friendly and economically favorable alternative waste management solutions is elaborated. The methodology combines data collection, operational analysis of the manufacturing processes, identification of wastes, and evaluation of waste reduction alternatives. The presented methodology is examined in a car battery manufacturing plant, which generates hazardous wastes composed of lead. It is aimed to decrease the wastes derived from the production so that the efficiency in raw materials usage is increased and the need for recycling the hazardous wastes is decreased.

A Sector Analysis for RFID Technologies: Fundamental and Technical Analysis for Financial Decision Making Problems

Automatic identification technologies have been used in a wide range of applications for reducing the amount of time and labor needed to input data and improving data accuracy. As an important automatic identification technology, radio frequency identification (RFID) technologies allow contactless reading and these technologies are particularly successful in manufacturing and other environments where traditional identification technologies such as bar codes can not perform well. By integrating the RFID technology into their business models, companies may save time, lower labor cost, improve products quality and provide better service. RFID is the wireless technology that uses RF communication to identify, track and manage objects and collect and store data. RFID technology enables companies to develop applications that create value by tracking and identifying objects, animals or people. Business applications of RFID technology can be seen in areas such as manufacturing, supply chain management, software integration, security systems, asset tracking and many others. RFID technology was predicted to be one of the “top ten” technologies in 2004 by CNN. Although, the RFID market is less than five years old, it has been applied to many different industries, from retail industry to logistics, or from healthcare to service business industry – and it is still growing. Particularly, RFID has fundamental influences on todays retailing and supply chain management for applications like asset tracking the inventory control and management. RFID technology also finds major application in mobile phones and is widely used in toll collection of highways, for payments in restaurants, vending machines, retail and parking lots. There are a wide range of RFID systems currently being used or being developed. Examples to these systems include but not limited to the following; automatic vehicle and personnel access control for security (Simpson, 2006), airport passenger and baggage tracking (Ferguson, 2006), tracing blood for cutting down errors such as giving patients wrong blood types (Ranger, 2006), payment process systems (Ramachandran, 2006), production control in manufacturing (Liu & Miao, 2006), transfusion medicine (Knels, 2006) real-time inventory control by automated identification of items in warehouses, tracking and management of physical files, tracking of books in the libraries (Shadid, 2005). For some other applications, interested reader is referred to (Finkenzeller, 2003; Smith, 2004). RFID solution providers claim that their technology and solutions bring significant benefits and have valuable advantages in practice. As new RFID solutions being developed and more RFID tags and equipments being used, these solutions will become more cost effective and RFID businesses are expected to grow rapidly. Since RFID is fairly new, it’s difficult to measure resulting sales increases or heightened customer satisfaction quotients. On the other hand, according to IDC estimation (IDC is a subsidiary of International Data Group, a leading technology media, research, and events company and provider of market intelligence, advisory services, and events for the information technology, telecommunications, and consumer technology markets), companies in the retail sector will spend nearly

Differential Algebraic Equations in Primal Dual Interior Point Optimization Methods

1.3 billion on RFID in their supply chain operations in 2008, compared to about

An Overview of Mean Field Theory in Combinatorial Optimization Problems

91.5 million in 2003 which corresponds to annual growth rate of 70 percent. In a similar look; the Wireless Data Research Group projected that the global market for RFID increased from

Neural Networks Approaches for Combinatorial Optimization Problems

1 billion in 2003 to

An Environmentally Integrated Manufacturing Analysis Combined with Waste Management in a Car Battery Manufacturing Plant

3 billion in 2007 (Asif & Mandviwalla, 2005). There are two major drivers of this growth. The first one is the adoption of RFID technology by major retailers and government agencies. The second one is the reduction in the price of RFID tags, readers, and IT systems required to deploy RFID. Given the huge potential of RFID technology, there has been a huge emergence of RFID specialty companies and the development of RFID practices within many market-leading companies. Due to huge emergence, it is desirable to make a sector analysis. In this study, we perform a sector analysis for RFID technologies for researchers and analysts. We investigate public RFID companies traded on the stock exchange markets, summarize their financial performance, describe their RF products, services, and applications, and perform fundamental and technical analysis.

Neural Networks for Combinatorial Optimization.

Primal dual Interior Point Methods (IPMs) generate points that lie in the neighborhood of the central trajectory. The key ingredient of the primal dual IPMs is the parameterization of the central trajectory. A new approach to the parameterization of the central trajectory is presented. Instead of parameterizing the central trajectory by the barrier parameter, it is parameterized by the time by describing a continuous dynamical system. Specifically, a new update rule based on the solution of an ordinary differential equation for the barrier parameter of the primal dual IPMs is presented. The resulting ordinary differential equation combined with the first order Karush‐Kuhn‐Tucker (KKT) conditions, which are algebraic equations, are called differential algebraic equations (DAEs). By solving DAEs, we find an optimal solution to the given problem.

Business Descriptions and Financial Performance Analysis of Public RFID Companies

In the last three decades, there has been significant interest in using mean field theory of statistical physics for combinatorial optimization. This has led to the development of powerful optimization techniques such as neural networks (NNs), simulated annealing (SA), and mean field annealing (MFA). MFA replaces the stochastic nature of SA with a set of deterministic equations named as mean field equations. The mean field equations depend on the energy function of the NNs and are solved at each temperature during the annealing process of SA. MFA advances to the optimal solution in a fundamentally different way than stochastic methods. The use of mean field techniques for the combinatorial optimization problems are reviewed in this study.

Development of a database and decision support system for performance evaluation of soccer players

Most of the engineering design problems and applications can be formulated as a nonlinear programming problem in which the objective function is nonlinear and has many local optima in its feasible region. It is desirable to find a local optimum that corresponds to the global optimum. The problem of finding the global optimum is known as the global optimization problem. Most such global optimization problems are difficult to solve. The main difficulties in finding the global optimum are that there are no operationally useful optimality conditions for identifying whether a point is indeed a global optimum, except in cases of special structured problems [33] and so it is computationally intensive to obtain the global optimum. Therefore, it is desirable and sometimes necessary to find a near global optimum in a reasonable time rather than obtaining the global optimum.