Applications of computational intelligence and fuzzy logic to manufacturing and service systems

2013 ◽  
Vol 66 (4) ◽  
pp. 1177
Keyword(s):  
Fuzzy Logic ◽  
Computational Intelligence ◽  
Service Systems

Computational Intelligence in Cross Docking

2014 ◽  
Vol 2 (1) ◽  
pp. 1-8
Author(s):  
Bo Xing
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Simulated Annealing ◽  
Tabu Search ◽  
Computational Intelligence ◽  
Simple Concept ◽  
Simulated Annealing Genetic Algorithm ◽  
Cross Docking ◽  
Open Questions ◽  
Key Issues

Cross docking is a practice in logistics with the main operations of goods flow directly from receiving to the shipping docks without stopping or being put away into storage. It is a simple concept to talk about, but a challenging one to implement. So far, many different approaches have been followed in order to improve the efficiency of a cross docking system. However, as the complexity increases, the use of computational intelligence (CI) in those problems is becoming a unique tool of imperative value. In this paper, different CI methods, such as Tabu search, simulated annealing, genetic algorithm, and fuzzy logic. The key issues in implementing the proposed approaches are discussed, and finally the open questions are highlighted.

Selected Papers from ISCIIA 2010

2011 ◽  
Vol 15 (3) ◽  
pp. 321-321
Author(s):  
Yasufumi Takama
Keyword(s):  
Fuzzy Logic ◽  
Computational Intelligence ◽  
Web Mining ◽  
Review Process ◽  
Industrial Applications ◽  
Future Research ◽  
Heilongjiang Province ◽  
Special Issue ◽  
Advanced Technologies ◽  
New Challenges

The 4th International Symposium on Computational Intelligence and Industrial Applications (ISCIIA2010), held at the Harbin University of Science and Technology in Heilongjiang Province, China, in August 2010 focused on advanced technologies for computational intelligence and industrial applications. A series of ISCIIA symposiums has provided a unique opportunity for the academic and industrial communities to address new challenges, share new-found solutions, and discuss directions for future research. Of the ISCIIA2010fs 50 papers, 11 outstanding papers have been selected for this special issue after fair and strict review process. Among this issuefs topics are fuzzy logic,Web mining, Kansei Information Processing (KIP), brain informatics, and human-centered systems. Given the importance of these topics to both the academic and industrial communities, this issue should contribute much to active exchange between both communities. As the Editor of this special issue, I thank all of the contributors and reviewers for their time and cooperation. Herefs hoping that the next ISCIIA, which is being held in Hokkaido, Japan, in 2012, will be as successful and fruitful as the 2010 symposium has been.

Computational Intelligence Techniques Driven Intelligent Agents for Web Data Mining and Information Retrieval

2004 ◽  
pp. 15-30 ◽  
Author(s):  
Masoud Mohammadian ◽  
Ric Jentzsch
Keyword(s):  
Fuzzy Logic ◽  
Computational Intelligence ◽  
Search Engines ◽  
Intelligent Agents ◽  
Intelligent System ◽  
Information Filtering ◽  
Evolutionary Computing ◽  
Building Blocks ◽  
Improved Performance ◽  
Search And Retrieval

The World Wide Web has added an abundance of data and information to the complexity of information for disseminators and users alike. With this complexity has come the problem of finding useful and relevant information. There is a need for improved and intelligent search and retrieval engines. Current search engines are primarily passive tools. To improve the results returned by searches, intelligent agents and other technology have the potential, when used with existing search and retrieval engines, to provide a more comprehensive search with an improved performance. This research provides the building blocks for integrating intelligent agents with current search engines. It shows how an intelligent system can be constructed to assist in better information filtering, gathering and retrieval. The research is unique in the way the intelligent agents are directed and in how computational intelligence techniques (such as evolutionary computing and fuzzy logic) and intelligent agents are combined to improve information filtering and retrieval. Fuzzy logic is used to access the performance of the system and provide evolutionary computing with the necessary information to carry out its search.

Computational Intelligence Using Type-2 Fuzzy Logic Framework

2013 ◽  
pp. 1-29
Author(s):  
A. Neogi ◽  
A.C. Mondal ◽  
S.K. Mandal
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Computational Intelligence ◽  
Fuzzy System ◽  
Research Topic ◽  
Student’S Performance ◽  
Interval Type ◽  
Exciting Area

In this chapter, the authors expand the notion of type-2 fuzzy sets. An introduction to standard and interval (type-2) fuzzy sets and systems is explained in the early part of the discussion. The chapter also covers the ideas of hybrid type-2 fuzzy system. Next, the authors study the applicability of type-2 fuzzy logic (FL) system in student’s performance in oral presentation as it is clearly new field of research topic and have an excellent opportunity to combine several fuzzy set method developed in the recent years. The proposed application shows the linkage of type-2 fuzzy system with TOPSIS. The present chapter also highlights the possible future directions for type-2 FL system research. By the end of the chapter, the authors hope that even those with little previous experience of fuzzy logic should be enabled to apply these methods in their own application areas and/or begin research in this fascinating and exciting area.

Sign in / Sign up

Export Citation Format

Share Document