This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from ...classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programming to the most modern methods based on bio-inspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.
This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from ...classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programming to the most modern methods based on bio-inspired metaheuristics. The featured papers invite readers to delve further into emerging optimization techniques and their real application to case studies such as conventional and renewable energy generation, distributed generation, transport and distribution of electrical energy, electrical machines and power electronics, network optimization, intelligent systems, advances in electric mobility, etc.
Guest Editorial Sideris, Constantine
IEEE transactions on microwave theory and techniques,
01/2024, Volume:
72, Issue:
8
Journal Article
Peer reviewed
I am delighted to introduce this Mini-Special Issue of the IEEE Transactions on Microwave Theory and Techniques (TMTT), which showcases selected papers from the International Conference on Numerical ...Electromagnetics, Multiphysics Modeling and Optimization (NEMO 2023). The NEMO 2023 took place on June 28–30, 2023 at the historic Fort Garry Hotel in the heart of Winnipeg, MB, Canada. NEMO is an annual international event founded in 2014 and has become a popular venue for exchanging novel ideas in computational and applied electromagnetics, multiphysics simulations, and optimization methods. Alternating between North America, Asia, and Europe, the conference brings together leading experts from academia and industry within the IEEE Microwave Theory and Techniques Society (IEEE MTT-S) and beyond. In particular, broad participation was achieved this year due to the availability of both online and in-person formats for attendance. The participants of the NEMO 2023 had the opportunity to attend the technical sessions and social events and to establish closer personal contacts. The NEMO 2023 was sponsored by the Price Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada, and industry partners Xpeedic, Ansys, CEMWorks, and Sonnet Software.
Additional Cover Liu, Jun; Li, Renfu; Wang, Kun ...
International journal for numerical methods in engineering,
11/2022, Volume:
123, Issue:
22
Journal Article
Peer reviewed
Open access
The cover image is based on the Research Article Net‐based thermal‐fluid model and hybrid optimization of cooling channels by Jun Liu et al., https://doi.org/10.1002/nme.7075.
Featured Cover Zhang, Yiming; Wang, Xueya; Wang, Xinquan ...
International journal for numerical methods in engineering,
11/2022, Volume:
123, Issue:
22
Journal Article
Peer reviewed
Open access
The cover image is based on the Research Article Virtual displacement based discontinuity layout optimization by Yiming Zhang et al., https://doi.org/10.1002/nme.7084.
Complex continuous optimization problems widely exist nowadays due to the fast development of the economy and society. Moreover, the technologies like Internet of things, cloud computing, and big ...data also make optimization problems with more challenges including
M
any-dimensions,
M
any-changes,
M
any-optima,
M
any-constraints, and
M
any-costs. We term these as 5-M challenges that exist in large-scale optimization problems, dynamic optimization problems, multi-modal optimization problems, multi-objective optimization problems, many-objective optimization problems, constrained optimization problems, and expensive optimization problems in practical applications. The evolutionary computation (EC) algorithms are a kind of promising global optimization tools that have not only been widely applied for solving traditional optimization problems, but also have emerged booming research for solving the above-mentioned complex continuous optimization problems in recent years. In order to show how EC algorithms are promising and efficient in dealing with the 5-M complex challenges, this paper presents a comprehensive survey by proposing a novel taxonomy according to the function of the approaches, including
reducing problem difficulty
,
increasing algorithm diversity
,
accelerating convergence speed
,
reducing running time
, and
extending application field
. Moreover, some future research directions on using EC algorithms to solve complex continuous optimization problems are proposed and discussed. We believe that such a survey can draw attention, raise discussions, and inspire new ideas of EC research into complex continuous optimization problems and real-world applications.
Over recent decades, the field of mobile robot path planning has evolved significantly, driven by the pursuit of enhanced navigation solutions. The need to determine optimal trajectories within ...complex environments has led to the exploration of diverse path planning methodologies. This paper focuses on a specific subset: Bio-inspired Population-based Optimization (BPO) methodologies. BPO methods play a pivotal role in generating efficient paths for path planning. Amidst the abundance of optimization approaches over the past decade, only a fraction of studies have effectively integrated these methods into path planning strategies. This paper focus is on the years 2014-2023, reviewing BPO techniques applied to mobile robot path planning challenges. Contributions include a comprehensive review of recent BPO methods in mobile robot path planning, along with an experimental methodology for method comparison under consistent conditions. This encompasses the same environment, initial conditions, and replicates. A multi-objective function is incorporated to evaluate optimization methods. The paper delves into key concepts, mathematical models, and algorithm implementations of examined optimization techniques. The experimental setup, methodology, and benchmarking performance results are discussed. In conclusion, this paper reviews recent BPO algorithms and introduces a standardized approach for benchmarking BPO algorithms, providing insights into their strengths and challenges in mobile robot path planning.