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2018专委会学术年会之IJBIC特刊征稿

2018/6/25 22:19:19 新闻来源：中国仿真学会智能仿真优化与调度专业委员会

《International Journal of Bio-Inspired Computation》为中科院二区期刊，2016-2017影响因子1.935。为了配合2018学术年会的召开，专委会副秘书长伍国华教授与副主任委员王凌教授等联合IJBIC期刊编委会组织了特刊"Intelligent Simulation Optimisation for Complex Systems"，欢迎大家踊跃投稿！

Special Issue on:
"Intelligent Simulation Optimisation for Complex Systems"

Guest Editors:
Prof. Guohua Wu and Prof. Jinjun Tang,
Central South University, China
Prof. Ling Wang,
Tsinghua University, China
Dr Huangke Chen,
National University of Defense Technology, China

Optimisation problems encuuntered in complex systems (e.g. manufacturing systems, energy systems, transportation systems and earth observation systems) are usually characterised by non-differentiable or discontinuous solution space, solution space increasing exponentially with problem size, the NP-Hard property, various complicated equality and inequality constraints, multi-modal, mixing variables, multiple optimisation objectives, uncertainties, and being without explicit problem expressions. Traditional mathematical programming methods are no longer completely efficient in resolving such optimisation problems in complex systems.

In contrast, intelligent simulation optimisation algorithms (ISOAs) appear to be competitive alternatives. During recent decades, research on intelligent simulation optimisation has progressed noticeably and gained fruitful rewards. Some classical and powerful ISOAs have been proposed and extensively investigated, including genetic algorithms, ant colony optimisation, particle swarm optimisation, differential evolution, tabu search, simulated annealing, variable neighbourhood search, etc.

Nevertheless, it is still a big challenge to further boost the efficiency, precision and robustness of ISOAs in dealing with complex systems. As a result, advanced techniques are required. For example, ensemble strategy is useful in designing versatile ISOAs by bringing together several types of algorithm components of respective advantages. In addition, it is widely agreed that strong while balanced exploration and exploitation capabilities are critical in a powerful ISOA. Moreover, evidence has frequently shown that the combination of problem domain knowledge and ISOAs could greatly improve the problem solving process. Furthermore, some other promising topics are attracting increasing attention, such as algorithm hybridisation, techniques for handling complex constraints, surrogate models for computationally expensive problems, adapted algorithm configuration, and distributed ISOAs.

Subject Coverage

Suitable topics include, but are not limited, to the following:

Efficient ISOAs for complex systems, including manufacturing systems, energy systems, transportation
systems and earth observation systems
Multi/many-objective ISOAs for complex systems
Distributed ISOAs for complex systems
Ensemble ISOAs for complex systems
Surrogated ISOAs for computationally expensive problems in complex systems
Combination of problem domain knowledge in complex systems and ISOAs to accelerate the optimisation process
Hybrid ISOAs with mathematical programming approaches for complex systems
Sophisticated constraint handling techniques for constrained optimisation problems in complex systems
ISOAs for complex systems with uncertainties and dynamics
ISOAs for optimisation problems with mixing variables in complex systems
Parameter and strategy adaptation in ISOAs
Balanced control strategies for exploitation and exploration in ISOAs

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely rewritten and if appropriate written permissions have been obtained from any copyright holders of the original paper).
All papers are refereed through a peer review process.
All papers must be submitted online. To submit a paper, please read our Submitting articles page.
If you have any queries concerning this special issue, please email Prof. Guohua Wu at
guohuawu.nudt@gmail.com.

Important Dates