… In this paper, we combine the attractor-based quantum method with MOEA/D to solve
multi-objective optimization problems. It takes efforts on two sides: (1) define a so-called global …

… emissions are expected to be optimized. These problems mentioned above are real multi-objective
optimization problems. And multi-objective optimization problems can be formulated …

… In this paper, we introduce it into solving interval multi-objective optimization problems. Let
\(\varOmega_{i} (t) = \left\{ {x_{j} |j = \arg \mathop {\hbox{min} }\nolimits_{k} D(x_{i} ,x_{k} )} \…

… many multi-objective optimization algorithms have been introduced by scholars. In particular,
evolutionary … known as evolutionary multi-objective optimization, such as the fast and elitist …

… Tanaka and Tanino later integrated the user’s association into an evolutionary multiobjective
optimization to propose a new system [25]. Instead of searching the entire pareto front, user …

… a multi-objective optimization problem, … multi-objective perspective, compared to the
more prevalent single-objective viewpoint.Motivated by this gap, we present a novel multi-objective …

… A new QEA algorithm is proposed to solve the multi-objective optimization problems. At the
same time, the combination of QEA algorithms with other algorithms has also obtained great …

… principles of quantum computing with EA to solve multi-objective optimization problems have
… algorithm that is able to solve continuous multi-objective optimization problem effectively. …

… The superposition and entanglement of the quantum state provides QIEAs with the … of
evolution [4]. Patvardhan et al. [4] proposed a parallel improved quantum inspired evolutionary …

… art by modifying two original, quantum-inspired algorithms to perform in continuous
search … step of multiobjective quantum optimization for quantum computers from quantum-inspired …