Seda Yanik

Fuzzy rule-based demand forecasting for dynamic pricing of a maritime company

In this study, the pricing problem of a transportation service provider company is considered. Our goal is to find optimal prices by using probabilistic dynamic programming. A fuzzy IF-THEN-rule based system is used to identify the demand levels under different prices and other characteristics of the journey. The results obtained by optimal price policies show that the revenue increases by applying dynamic pricing policy instead of fixed pricing. Thus, the diversification of pricing policies under different conditions is beneficial for the company.

A new VRPPD model and a hybrid heuristic solution approach for e-tailing

We analyze a business model for e-supermarkets to enable multi-product sourcing capacity through co-opetition (collaborative competition). The logistics aspect of our approach is to design and execute a network system where “premium” goods are acquired from vendors at multiple locations in the supply network and delivered to customers. Our specific goals are to: (i) investigate the role of premium product offerings in creating critical mass and profit; (ii) develop a model for the multiple-pickup single-delivery vehicle routing problem in the presence of multiple vendors; and (iii) propose a hybrid solution approach. To solve the problem introduced in this paper, we develop a hybrid metaheuristic approach that uses a Genetic Algorithm for vendor selection and allocation, and a modified savings algorithm for the capacitated VRP with multiple pickup, single delivery and time windows (CVRPMPDTW). The proposed Genetic Algorithm guides the search for optimal vendor pickup location decisions, and for each generated solution in the genetic population, a corresponding CVRPMPDTW is solved using the savings algorithm. We validate our solution approach against published VRPTW solutions and also test our algorithm with Solomon instances modified for CVRPMPDTW.

Trading-up on unmet expectations? Evaluating consumers’ expectations in online premium grocery shopping logistics

Geography and retail store locations are inherently bound together; this study links food retail changes to systemic logistics changes in an emerging market. The later include raising income and education, access to a wide range of technologies, traffic and transport difficulties, lagging retail provision, changing family structure and roles, as well as changing food culture and taste. The study incorporates demand for premium products defined by Kapferer and Bastien [2009b. The Luxury Strategy. London: Kogan Page] as comprising a broad variety of higher quality and unique or distinctive products and brands including in grocery organic ranges, healthy options, allergy free selections, and international and gourmet/specialty products through an online grocery model (n = 356) that integrates a novel view of home delivery in Istanbul. More importantly from a logistic perspective our model incorporates any products from any online vendors broadening the range beyond listed items found in any traditional online supermarkets. Data collected via phone survey and analysed via structural equation modelling suggest that the offer of online premium products significantly affects consumers’ delivery logistics expectations. We discuss logistics operations and business management implications, identifying the emerging geography of logistic models which respond to consumers’ unmet expectations using multiple sourcing and consolidation points.

Intelligent Decision Making in Quality Management

This book presents recently developed intelligent techniques with applications and theory in the area of quality management. The involved applications of intelligence include techniques such as fuzzy sets, neural networks, genetic algorithms, etc. The book consists of classical quality management topics dealing with intelligent techniques for solving the complex quality management problems. The book will serve as an excellent reference for quality managers, researchers, lecturers and postgraduate students in this area. The authors of the chapters are well-known researchers in the area of quality management.

A Literature Survey on Metaheuristics in Production Systems

Typical problems in production systems are suboptimal production scheduling, long manufacturing lead times, inefficient inventory control, low work center utilization, etc. The solutions of these problems may need complex techniques while the classical techniques are insufficient to solve them. In this chapter we first classified the problems which may be faced in production systems and then the solution techniques called metaheuristics. Based on the keywords production problems and metaheuristics, our search was resulted in about 6,500 papers. The results have been summarized by tabular forms and graphical figures. The journals frequently publishing these papers have been also classified.

A Framework for the Performance Evaluation of an Energy Blockchain

In this study, we first discuss the disruption and its impacts on the power and utilities sector. We identify the drivers of the disruption and the impact it will make on the sector. Then, as one of the drivers of disruption, we examine the blockchain technology, its features, benefits and limitations. We identify a performance evaluation framework for a power and utilities blockchain, in a distributed generation setting. Finally, we evaluate the performance factors’ interrelationships on the performance of the blockchain system and investigate the importance and cause-effect groups of the factors.

Project Portfolio Selection for the Digital Transformation Era

By bringing various technological advances together, Industry 4.0 promises production systems to boost in productivity. The transformation of the existing production systems into an Industry 4.0 factory is a strategic and long-term undertaking which needs a high capital investment, training of personnel and change of the environment and the culture in almost all of the functions of the value chain. Thus, it is required to be planned well by the companies. To be successful in the Industry 4.0 era, companies will not only have to simultaneously execute interdependent projects, but also require to perform project portfolio selection task in multi-dimensional environments in the presence of high uncertainty. Since determining optimal project portfolio for digital transformation among various project alternatives demands the consideration of multiple constraints and interdependencies, an integer programming model is proposed to address this problem in this chapter. To demonstrate its effectiveness and practicality, the proposed optimization model is applied to the Industry 4.0 project alternatives of an automotive manufacturer.

Intelligent Process Control Using Control Charts—II: Control Charts for Attributes

Shewhart’s control charts are used when you have enough and exact observed data. In case of incomplete and vague data, they can be still used by the help of the fuzzy set theory. In this chapter, we develop the fuzzy control charts for variables, which are namely \( \overline{X} \) and R and \( \overline{X} \) and S charts. Triangular fuzzy numbers have been used in the development of these charts. Unnatural patterns have been examined under fuzziness. Besides, fuzzy EWMA charts have been also developed in this chapter. For each fuzzy case, we present a numerical example.

Intelligent Decision Making Techniques in Quality Management: A Literature Review

Intelligent techniques present optimum or suboptimal solutions to complex problems, which cannot be solved by the classical mathematical programming techniques. The aim of this chapter is to review the intelligent decision making literature in order to reveal their usage in quality problems. We first classify the intelligent techniques and then present graphical illustrations to show the status of these techniques in the solutions of quality problems. These graphs display the publishing frequencies of the intelligent quality management papers with respect to their countries, universities, journals, authors, types (whether it is a conference paper, book chapter, journal 1 paper, etc.)

The Role of Computational Intelligence in Experimental Design: A Literature Review

Experimental design (DOE) is a well-developed methodology that has been frequently adopted for different purposes in a wide range of fields such as control theory, optimization, and intelligent decision making. The main objective of DOE is to best select experiments to estimate a set of parameters while consuming as little resources as possible. The enrichment of literature on computational intelligence has supported DOE to extend its sphere of influence in the past two decades. Specifically, the most significant progress has been observed in the area of optimal experimentation, which deals with the calculation of the best scheme of measurements so that the information provided by the data collected is maximized. Nevertheless, determining the design that captures the true relationship between the response and control variables is the most fundamental objective. When deciding whether a design is better (or worse) than another one, usually a criterion is utilized to make an objective distinction. There is a wide range of optimality criteria available in the literature that has been proposed to solve theoretical or practical problems stemming from the challenging nature of optimal experimentation. This study focuses on the most recent applications of DOE related to heuristic optimization, fuzzy approach, and artificial intelligence with a special emphasis on the optimal experimental design and optimality criteria.