Theory of fuzzy integrals and its applications

Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the latest research advances in this field.

Optimization methods applied to renewable and sustainable energy: A review

The purpose of this paper is to conduct a state-of-the-art review of the ongoing research on the Industry 4.0 phenomenon, highlight its key design principles and technology trends, identify its architectural design and offer a strategic roadmap that can serve manufacturers as a simple guide for the process of Industry 4.0 transition.,The study performs a systematic and content-centric review of literature based on a six-stage approach to identify key design principles and technology trends of Industry 4.0. The study further benefits from a comprehensive content analysis of the 178 documents identified, both manually and via IBM Watson’s natural language processing for advanced text analysis.,Industry 4.0 is an integrative system of value creation that is comprised of 12 design principles and 14 technology trends. Industry 4.0 is no longer a hype and manufacturers need to get on board sooner rather than later.,The strategic roadmap presented in this study can serve academicians and practitioners as a stepping stone for development of a detailed strategic roadmap for successful transition from traditional manufacturing into the Industry 4.0. However, there is no one-size-fits-all strategy that suits all businesses or industries, meaning that the Industry 4.0 roadmap for each company is idiosyncratic, and should be devised based on company’s core competencies, motivations, capabilities, intent, goals, priorities and budgets.,The first step for transitioning into the Industry 4.0 is the development of a comprehensive strategic roadmap that carefully identifies and plans every single step a manufacturing company needs to take, as well as the timeline, and the costs and benefits associated with each step. The strategic roadmap presented in this study can offer as a holistic view of common steps that manufacturers need to undertake in their transition toward the Industry 4.0.,The study is among the first to identify, cluster and describe design principles and technology trends that are building blocks of the Industry 4.0. The strategic roadmap for Industry 4.0 transition presented in this study is expected to assist contemporary manufacturers to understand what implementing the Industry 4.0 really requires of them and what challenges they might face during the transition process.

https://www.emerald.com/insight/content/doi/10.1108/JMTM-02-2018-0057/full/pdf

The future of manufacturing industry: a strategic roadmap toward Industry 4.0

Two decades was systematically reviewed on fuzzy MCDM techniques from 1994 to 2014.The database for review was 403 papers from more than 150 high-ranking journals.403 scholarly papers were grouped in four different main fields.Papers were classified based on utilizing, developing and proposing research papers. MCDM is considered as a complex decision-making tool involving both quantitative and qualitative factors. In recent years, several fuzzy FMCDM tools have been suggested to choosing the optimal probably options. The purpose of this paper is to review systematically the applications and methodologies of the fuzzy multi decision-making (FMCDM) techniques. This study reviewed a total of 403 papers published from 1994 to 2014 in more than 150 peer reviewed journals (extracted from online databases such as ScienceDirect, Springer, Emerald, Wiley, ProQuest, and Taylor & Francis). According to experts' opinions, these papers were grouped into four main fields: engineering, management and business, science, and technology. Furthermore, these papers were categorized based on authors, publication date, country of origin, methods, tools, and type of research (FMCDM utilizing research, FMCDM developing research, and FMCDM proposing research). The results of this study indicated that, in 2013, scholars have published papers more than other years. In addition, hybrid fuzzy MCDM in the integrated method and fuzzy AHP in the individual section were ranked as the first and second methods in use. Additionally, Taiwan was ranked as the first country that contributed to this survey, and engineering was ranked as the first field that has applied fuzzy DM tools and techniques.

Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014

An effective way for managing and controlling a large number o f inventory items or stock keeping units (SKUs) is the inventory classification. Tradi tional ABC analysis which based on only a single criterion is commonly used for classification of SKU s. However, we should consider inven- tory classification as a multi-criteria problem in practice . In this study, a new method of Evaluation based on Distance from Average Solution (EDAS) is introduced for multi-criteria inventory clas- sification (MCIC) problems. In the proposed method, we use po sitive and negative distances from the average solution for appraising alternatives (SKUs). To represent performance of the proposed method in MCIC problems, we use a common example with 47 SKUs. Comparing the results of the proposed method with some existing methods shows the good performance of it in ABC classifica- tion. The proposed method can also be used for multi-criteria decision-making (MCDM) problems. A comparative analysis is also made for showing the validity and stability of the proposed method in MCDM problems. We compare the proposed method with VIKOR, TOPSIS, SAW and COPRAS methods using an example. Seven sets of criteria weights and Spearman's correlation coefficient are used for this analysis. The results show that the proposed method is stable in different weights and well consistent with the other methods.

/pdf/multi-criteria-inventory-classification-using-a-new-method-5220ny8i4c.pdf

Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS)

A comparative analysis for multiattribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process

A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system

Analytical HFACS for investigating human errors in shipping accidents.

Although there have been quite a number of theoretical and practical studies where axiomatic design (AD) principles have been used in the last few years, there is a lack of a comprehensive literature survey which evaluates and classifies these papers. This study provides a recognizable overview of literature on AD principles from the past 20 years and introduces a novel classification scheme covering 63 papers. Each article was classified into four main groups, namely the type of the axiom, the application area, the method, and the evaluation type. Findings of our paper indicate that most of the studies in the literature are application-based papers which use typically the independence axiom. While product design is put forward in the application area, the crisp approach is widely used as an evaluation type. A rise in the fuzzy evaluation based research studies using the information axiom for multi-attribute decision making problems has also been noticed.

Review: Applications of axiomatic design principles: A literature review

Axiomatic design (AD) provides a framework to describe design objects and a set of axioms to evaluate relations between intended functions and means by which they are achieved. Fuzziness in axiomatic design (FAD) has been handled by some researchers to evaluate alternatives under fuzzy environment. In this paper, three important tolls are added FAD method so as to supply its deficiency. The first one is the hierarchy which has the ability of taking the hierarchical structures into account. The second is the crisp toll which has the ability of taking the positive information into consideration under fuzzy environment. The last one is the ranking ability. As a matter of fact, FAD method is developed to be used for the solution of all manners of multi-attribute decision making problems. Moreover, an application to a teaching assistant selection problem is made to show the usability of the developed method.

Selcuk Cebi

Papers

A comparative analysis for multiattribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process

A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system

Analytical HFACS for investigating human errors in shipping accidents.

Review: Applications of axiomatic design principles: A literature review

A new multi-attribute decision making method: Hierarchical fuzzy axiomatic design