Results 101 to 110 of about 65,077 (195)
This paper systematically evaluates and compares three well-engineered and popular multi-objective optimization algorithms for the design of switched reluctance machines.
Shen Zhang +3 more
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In metaheuristic multi-objective optimization, the term effectiveness is used to describe the performance of a metaheuristic algorithm in achieving two main goals—converging its solutions towards the Pareto front and ensuring these solutions are well ...
Kanak Kalita +4 more
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To address the complexity of multi-constraint multi-objective optimization problems (mCMOPs), this paper proposes a novel multi-population evolutionary algorithm (MOEA).
Xinyue Xiang +3 more
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In recent years, researchers have taken the many-objective optimization algorithm, which can optimize 5, 8, 10, 15, 20 objective functions simultaneously, as a new research topic.
Jiale Zhao +5 more
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Fair Cost Allocation in Energy Communities Under Forecast Uncertainty
Energy communities (ECs) are an increasingly studied path toward improving prosumer coordination. A central challenge of ECs is to allocate cost savings fairly to members. While many allocation mechanisms have been developed, existing literature does not
Michael Eichelbeck, Matthias Althoff
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The optimal scheduling of DES is to solve a multi-objective optimization problem (MOP) with complex constraints. However, the potential contradiction between multiple optimization objectives leads to the diversity of feasible solutions, which has a ...
Suliang Ma +3 more
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Solving Hard Multiobjective Problems with a Hybridized Method
This paper presents a hybrid method to solve hard multiobjective problems. The proposed approach adopts an epsilon-constraint method which uses a Particle Swarm Optimizer to get points near of the true Pareto front. In this approach, only few points will
Leticia Cagnina, Susana Cecilia Esquivel
doaj
Improved multi-objective decision-making in manufacturing processes through uncertainty quantification and robust pareto front modelling. [PDF]
De Temmerman A, Verbeke M.
europepmc +1 more source
A multi objective optimization framework for smart parking using digital twin pareto front MDP and PSO for smart cities. [PDF]
Sahu D +5 more
europepmc +1 more source
Pareto-DQN: Approximating the Pareto front in complex multi-objective decision problems
In many real-world problems, one needs to care about multiple objectives. These objectives can be contradicting and, depending on the decision maker, the different compromises will be ranked differently. In this preliminary work, we propose a novel algorithm: Pareto-DQN, that will estimate the Pareto front of complex environment, with a high ...
Reymond, Mathieu, Nowe, Ann
openaire +1 more source

