This paper describes a robust version to the TEAM 22 benchmark optimization problem and presents the methodology WCSA (worst case scenario approximation) to solve this problem and other similar cases. The robust multi-objective TEAM 22 model was built from its classical configuration by assuming the imprecisions in the design space. General and specific robust optimization formulas were developed to elaborate WCSA approach. WCSA adds an uncertainty parameter in the objective and constraint functions to perform the role of the system’s imprecisions. A multi-objective genetic algorithm approach was chosen to deal with the robust formulation and to find out the set of robust minimizers that matches with the problem requirements. The behavior o...
Abstract: Robust design optimization (RDO) uses statistical de-cision theory and optimization techni...
In electromagnetic design, uncertainties in design variables are inevitable, thus in addition to pur...
International audienceMotors design optimization using multiobjective genetic algorithms is an effic...
The optimal design of electromagnetic devices is often performed by balancing conflicting objectives...
Topology optimization (TO), which is a design optimization technique that does not require design pa...
This paper proposes a new benchmark for multi-objective optimization. A solution is furnished which ...
New solutions to a recently proposed benchmark TEAM problem for Pareto optimisation are presented. I...
The study presented in this article reformulates and generalizes the TEAM benchmark, originally prop...
Although probabilistic optimization methods based on genetic algorithm (GA) provides accurate result...
The study presented in this article reformulates and generalizes the TEAM benchmark, originally prop...
In optimization studies including multi-objective optimization, the main focus is placed on finding ...
A common trade-off in engineering design is between the reliability of a system and its expected per...
Uncertainties in the design variables of non-linear engineering optimization problems are often negl...
The role of the parameters uncertainness in the optimal design of electromagnetic devices is discuss...
Due to construction tolerances, the performances of actual electromagnetic devices differ from those...
Abstract: Robust design optimization (RDO) uses statistical de-cision theory and optimization techni...
In electromagnetic design, uncertainties in design variables are inevitable, thus in addition to pur...
International audienceMotors design optimization using multiobjective genetic algorithms is an effic...
The optimal design of electromagnetic devices is often performed by balancing conflicting objectives...
Topology optimization (TO), which is a design optimization technique that does not require design pa...
This paper proposes a new benchmark for multi-objective optimization. A solution is furnished which ...
New solutions to a recently proposed benchmark TEAM problem for Pareto optimisation are presented. I...
The study presented in this article reformulates and generalizes the TEAM benchmark, originally prop...
Although probabilistic optimization methods based on genetic algorithm (GA) provides accurate result...
The study presented in this article reformulates and generalizes the TEAM benchmark, originally prop...
In optimization studies including multi-objective optimization, the main focus is placed on finding ...
A common trade-off in engineering design is between the reliability of a system and its expected per...
Uncertainties in the design variables of non-linear engineering optimization problems are often negl...
The role of the parameters uncertainness in the optimal design of electromagnetic devices is discuss...
Due to construction tolerances, the performances of actual electromagnetic devices differ from those...
Abstract: Robust design optimization (RDO) uses statistical de-cision theory and optimization techni...
In electromagnetic design, uncertainties in design variables are inevitable, thus in addition to pur...
International audienceMotors design optimization using multiobjective genetic algorithms is an effic...