Special Session


Dynamic Multi-objective Optimization (DMOO 2018)

Many real-world engineering optimization problems not only require the simultaneous optimization of a number of objective functions, but also need to track the changing optimal solutions. These problems are called: Dynamic multi-objective optimization (DMOO) problems. Here, where either the objective functions or the constraints change over time, an optimization algorithm should be able to find, and track the changing set of optimal solutions and approximate the time-varying true Pareto front. Therefore, the DMOO algorithm also has to deal with the problems of a lack of diversity and outdated memory.

The main goal of this special session is to emphasize the newest techniques in solving dynamic multi-objective optimization problems and handling the current issues. So the session aims at providing a forum for researchers in the area of DMOO to exchange new ideas and submit their original and unpublished work. Topics of interest include, but are not limited to:

• Theoretical analysis, convergence criterion, and complexity of DMOO algorithms
• Handling outlier detection, complex and deceiptive solutions, and constraints of DMOO
• Algorithms, benchmark functions, and performance measures of DMOO
• Dynamic many-objective optimization
• Uncertainty and noisy fitness functions in DMOO
• Hybrid algorithms of DMOO
• Real-world applications of DMOO (Biomedical engineering, Modeling, Big data, …)

Special Session Organizers

Prof. Mohammad Teshnehlab
Full Professor, Electrical Engineering Faculty,
K. N. Toosi University of Technology, Tehran, Iran
E-mail: teshnehlab@eetd.kntu.ac.ir

Dr. Hamid Beigy
Associate Professor, Department of Computer Engineering,
Sharif University of Technology, Tehran, Iran
E-mail: beigy@sharif.edu

Dr. Maysam Orouskhani
PhD of Artificial Intelligence,
Science and Research Branch of Islamic Azad University, Tehran, Iran
E-mail: maysam.orouskhani@srbiau.ac.ir

Important dates

Submission of papers: 1 March 2018
Notification of acceptance: 15 April 2018
Camera-ready papers: 30 April 2018
Registration & payment: 15 May 2018
Conference date: 3-5 July 2018

Submission

All contributions should be original and not published elsewhere or intended to be published during the review period. Authors are invited to submit their papers electronically in pdf format, through EasyChair. All the special sessions are centralized as tracks in the same conference management system as the regular papers. Therefore, to submit a paper please activate the following link and select the track: DMOO 2018: Special Session on Dynamic Multi-objective Optimization: https://easychair.org/conferences/?conf=inista2018

Paper format: Papers must be prepared using  IEEE templates for conference proceedings.

Page limit: The maximum page limit is 6 inclusive of figures and tables. INISTA will offer the option to buy limited number of extra pages for submission.

Language: The official language for the conference is English. Less than satisfactory English usage may form the sole basis for rejection of a paper and omission of any such final paper version from the conference proceedings. Authors whose native language is not English are encouraged to check their papers for proper English spelling and grammar using tools such as English grammar checkers available with most word processing application software. Alternatively, proofreading support from a native English-speaking colleague or technical editor may suffice. Some authors may be interested in the paid service available at the following link: http://www.prof-editing.com/ieee/ for the final version of the paper.

Program Committee (tentative)

Mohammad Teshnehlab, K. N. Toosi University of Technology
Hamid Beigy, Sharif University of Technology
Maysam Orouskhani, Science and Research Branch of Islamic Azad University
Ran Cheng, University of Birmingham,
Arrchana Murugananthama, National University of Singapore
Maxime Clement, Ichise Laboratory National Institute of Informatics
Yasin Orouskhani, Data Engineer at RAHNAMA Co
Renzhi Chen, University of Birmingham