Optimization can be easily found in our daily life, almost everywhere and with many applications. Choosing the shortest path from home to office or working place, with the purpose of spending less ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

Large-scale sparse multi-objective optimization problems are prevalent in numerous real-world scenarios, such as neural network training, sparse regression, pattern mining and critical node detection, ...