IEEE CEC-33 Real-World and Industry Applications of Evolutionary Computation
CEC-RIAEC 2020
- URL: https://wcci2020.org/cec-sessions/
- Event Date: 2020-07-19 ~ 2020-07-24
- Submission Date: 2020-01-15
- Location: Glasgow, United Kingdom
Call for Papers:
CEC 2020 Special Session on "Real-World and Industry Applications of Evolutionary Computation"
IEEE World Congress on Computational Intelligence (WCCI)
CEC Real-World and Industry Applications of Evolutionary Computation
During the last three decades, evolutionary computation (EC) has been widely used for solving complex real-world problems. These techniques are getting popular these days for business, management, and design optimization as they are commonly deal with complex problems without explicit formula. The main focus of this special session would be on the EC techniques applications to complex real-world problems.
Scope and Topics:
Management, Scheduling, design, maintenance and monitoring real-world and industrial systems, such as factories and companies, are challenging issues and involve several constraints. In order to find a practical solution, most real-world problems should be formulated as discrete or mixed variable optimization problems. Furthermore, finding efficient and lower cost procedures for frequent use of the system is crucially important. Mining and interpretation of the response data are other major issues that need advanced computation. Stochastic nature of most real-world systems (e.g. stock market) make these analyses even more complex. While several solutions are proposed to tackle the issues mentioned above, there is still a serious need for more cost-effective approaches. Due to their complexity, the real-world problems are difficult to solve using derivative-based and local optimization algorithm. A viable solution to cope with this limitation is to employ global optimization algorithms, such as the EC techniques. In the recent past, EC and its branches have been used to solve complex real-world problems that cannot be solved using conventional methods. The other important issue is that several aspects can be considered to optimize systems simultaneously such as time, cost, quality, risk, etc. Therefore, more than one objective should usually be considered for optimizing a real-world system. This is while there are usually conflicts between the considered objectives, such as cost-quality. In this case, the multi-objective optimization concept offers major advantages over the traditional mathematical algorithms. More specifically, evolutionary multi-objective optimization (EMO) is known as a reliable way to handle these problems in the industrial domain.
This special session strives to gather the latest development of EC applications in real-world systems. On this basis, this special session includes key applications of EC on different disciplines such as business, management, engineering optimization, etc. Topics to be included are evolutionary optimization and multi-objective algorithms, as well as evolutionary (big) data mining algorithms. The methods of interest in real-world domains include (but not limited to):
• Operation management
• Planning and Scheduling problem
• Maintenance and Monitoring optimization
• Design optimization (topology, configuration, etc.)
• Optimizing transportation systems
• Stock market prediction
• Portfolio Optimization
• Layout problem
• Simulation optimization (grey/black box problems)
• Large-scale real-world systems
• Multi and many objective real-world problems
• Expensive real-world problem (limited budget)
• Surrogate-assisted systems
• Highly constrained problems
• Embedding knowledge
• Robust real-world optimization
• Probabilistic real-world optimization
• Bi-level real-world optimization
• real-world (big) data mining
• Smart cities
• Internet of things
• Uncertain and noisy systems
Important Dates:
Paper submission due: Jan 15th 2020
Notification of acceptance: Mar 15th 2020
Author registration deadline: Apr 15th 2020
Paper Submission:
Please select the "Real-World and Industry Applications of Evolutionary Computation" as the Main research topic, at:
https://ieee-cis.org/conferences/cec2020/upload.php
Organizers:
Prof. Amir H. Gandomi, University of Technology Sydney, Australia, e-mail: gandomi@uts.edu.au
Dr. Mohammad Nabi Omidvar, University of Leeds, UK, e-mail: m.n.omidvar@leeds.ac.uk
Prof. Kalyanmoy Deb, Michigan State University, USA, e-mail: kdeb@egr.msu.edu
Program Committee:
Mohammad-R Akbarzadeh-T, Ferdowsi University of Mashhad
Amir H. Alavi, University of Pittsburgh
Simon James Fong, University of Macau
Saeed Gholizadeh, Urmia University
Thomas Hanne, University of Applied Sciences and Arts Northwestern
Ali Kaveh, Iran University of Science & Technology
Saeid Kazemzadeh Azad, Atilim University
Nikos D. Lagaros, National Technical University Athens
Szymon Lukasik, AGH University of Science and Technology
Krzysztof Michalak, Wroclaw University of Economics
Seyedali Mirjalili, Torrens University Australia
Jonas Schwaab, ETH Zurich
Amirhessam Tahmassebi, Florida State University
Siamak Talatahari, University of Tabriz
Gregorio Toscano Pulido, CINVESTAV-IPN
Gai-Ge Wang, Ocean University of China
CEC 2020 Special Session on "Real-World and Industry Applications of Evolutionary Computation"
IEEE World Congress on Computational Intelligence (WCCI)
CEC Real-World and Industry Applications of Evolutionary Computation
During the last three decades, evolutionary computation (EC) has been widely used for solving complex real-world problems. These techniques are getting popular these days for business, management, and design optimization as they are commonly deal with complex problems without explicit formula. The main focus of this special session would be on the EC techniques applications to complex real-world problems.
Scope and Topics:
Management, Scheduling, design, maintenance and monitoring real-world and industrial systems, such as factories and companies, are challenging issues and involve several constraints. In order to find a practical solution, most real-world problems should be formulated as discrete or mixed variable optimization problems. Furthermore, finding efficient and lower cost procedures for frequent use of the system is crucially important. Mining and interpretation of the response data are other major issues that need advanced computation. Stochastic nature of most real-world systems (e.g. stock market) make these analyses even more complex. While several solutions are proposed to tackle the issues mentioned above, there is still a serious need for more cost-effective approaches. Due to their complexity, the real-world problems are difficult to solve using derivative-based and local optimization algorithm. A viable solution to cope with this limitation is to employ global optimization algorithms, such as the EC techniques. In the recent past, EC and its branches have been used to solve complex real-world problems that cannot be solved using conventional methods. The other important issue is that several aspects can be considered to optimize systems simultaneously such as time, cost, quality, risk, etc. Therefore, more than one objective should usually be considered for optimizing a real-world system. This is while there are usually conflicts between the considered objectives, such as cost-quality. In this case, the multi-objective optimization concept offers major advantages over the traditional mathematical algorithms. More specifically, evolutionary multi-objective optimization (EMO) is known as a reliable way to handle these problems in the industrial domain.
This special session strives to gather the latest development of EC applications in real-world systems. On this basis, this special session includes key applications of EC on different disciplines such as business, management, engineering optimization, etc. Topics to be included are evolutionary optimization and multi-objective algorithms, as well as evolutionary (big) data mining algorithms. The methods of interest in real-world domains include (but not limited to):
• Operation management
• Planning and Scheduling problem
• Maintenance and Monitoring optimization
• Design optimization (topology, configuration, etc.)
• Optimizing transportation systems
• Stock market prediction
• Portfolio Optimization
• Layout problem
• Simulation optimization (grey/black box problems)
• Large-scale real-world systems
• Multi and many objective real-world problems
• Expensive real-world problem (limited budget)
• Surrogate-assisted systems
• Highly constrained problems
• Embedding knowledge
• Robust real-world optimization
• Probabilistic real-world optimization
• Bi-level real-world optimization
• real-world (big) data mining
• Smart cities
• Internet of things
• Uncertain and noisy systems
Important Dates:
Paper submission due: Jan 15th 2020
Notification of acceptance: Mar 15th 2020
Author registration deadline: Apr 15th 2020
Paper Submission:
Please select the "Real-World and Industry Applications of Evolutionary Computation" as the Main research topic, at:
https://ieee-cis.org/conferences/cec2020/upload.php
Organizers:
Prof. Amir H. Gandomi, University of Technology Sydney, Australia, e-mail: gandomi@uts.edu.au
Dr. Mohammad Nabi Omidvar, University of Leeds, UK, e-mail: m.n.omidvar@leeds.ac.uk
Prof. Kalyanmoy Deb, Michigan State University, USA, e-mail: kdeb@egr.msu.edu
Program Committee:
Mohammad-R Akbarzadeh-T, Ferdowsi University of Mashhad
Amir H. Alavi, University of Pittsburgh
Simon James Fong, University of Macau
Saeed Gholizadeh, Urmia University
Thomas Hanne, University of Applied Sciences and Arts Northwestern
Ali Kaveh, Iran University of Science & Technology
Saeid Kazemzadeh Azad, Atilim University
Nikos D. Lagaros, National Technical University Athens
Szymon Lukasik, AGH University of Science and Technology
Krzysztof Michalak, Wroclaw University of Economics
Seyedali Mirjalili, Torrens University Australia
Jonas Schwaab, ETH Zurich
Amirhessam Tahmassebi, Florida State University
Siamak Talatahari, University of Tabriz
Gregorio Toscano Pulido, CINVESTAV-IPN
Gai-Ge Wang, Ocean University of China
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