Combinatorial optimisation is a fundamental field in applied mathematics and computer science that focuses on finding an optimal object from a finite set of objects. In this context, problems are ...

The proposed algorithm combines variational scheduling with post-processing to achieve near-optimal solutions to combinatorial optimization problems with constraints within the operation time of ...

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 ...

The paper intends to give a survey on some important aspects of optimization problems with infinitely many constraints. We consider the structure of the problem, optimality conditions, Newton methods ...

We might be witnessing the start of a new computing era where AI, cloud and quantum begin to converge in ways that redefine data processing and problem-solving.

This research explores how user-defined constraints affect the efficiency and effectiveness of multi-objective evolutionary algorithm (MOEA) optimization in water resources. Constraints in MOEA ...

where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...