An easy-to-use real-world multi-objective optimization problem suite
Although synthetic test problems are widely used for the performance assessment of
evolutionary multi-objective optimization algorithms, they are likely to include unrealistic …
evolutionary multi-objective optimization algorithms, they are likely to include unrealistic …
Optimal design of the bearingless induction motor
The bearingless version of the induction motor (IM) has unacceptable performance for high
speed or significant power applications. This is due to design challenges that are unique to …
speed or significant power applications. This is due to design challenges that are unique to …
Distance-based subset selection for benchmarking in evolutionary multi/many-objective optimization
A number of real-world problems involve extremization of multiple conflicting objectives,
referred to as multiobjective optimization problems. Multiobjective evolutionary algorithms …
referred to as multiobjective optimization problems. Multiobjective evolutionary algorithms …
Comparison of multi-objective evolutionary algorithms applied to watershed management problem
S Wang, Y Wang, Y Wang, Z Wang - Journal of environmental management, 2022 - Elsevier
Simulation-based optimization (S–O) frameworks are effective in develo** cost-effective
watershed management strategies, where optimization algorithms have substantial effect on …
watershed management strategies, where optimization algorithms have substantial effect on …
Fast greedy subset selection from large candidate solution sets in evolutionary multiobjective optimization
Subset selection plays an important role in the field of evolutionary multiobjective
optimization (EMO). Especially, in an EMO algorithm with an unbounded external archive …
optimization (EMO). Especially, in an EMO algorithm with an unbounded external archive …
[書籍][B] Archiving strategies for evolutionary multi-objective optimization algorithms
O Schütze, C Hernández - 2021 - Springer
This book presents an overview of several archiving strategies we have developed over the
last years dealing with approximations of the solution sets of multi-objective optimization …
last years dealing with approximations of the solution sets of multi-objective optimization …
Simultaneous optimization of design and maintenance for systems using multi-objective evolutionary algorithms and discrete simulation
When projecting and building new industrial facilities, getting integrated design alternatives
and maintenance strategies are of critical importance to achieve the physical assets optimal …
and maintenance strategies are of critical importance to achieve the physical assets optimal …
Running time analysis of MOEA/D with crossover on discrete optimization problem
Decomposition-based multiobjective evolutionary algorithms (MOEAs) are a class of popular
methods for solving multiobjective optimization problems (MOPs), and have been widely …
methods for solving multiobjective optimization problems (MOPs), and have been widely …
On the combined impact of population size and sub-problem selection in MOEA/D
This paper intends to understand and to improve the working principle of decomposition-
based multi-objective evolutionary algorithms. We review the design of the well-established …
based multi-objective evolutionary algorithms. We review the design of the well-established …
Multi-objective multi-facility green manufacturing closed-loop supply chain under uncertain environment
Purpose Today's, supply chain production and distribution of products to improve the
customer satisfaction in the shortest possible time by paying the minimum cost, has become …
customer satisfaction in the shortest possible time by paying the minimum cost, has become …