We use heuristics to solve computationally difficult problems where optimal solutions are too expensive to deploy, hard to manage, or otherwise inefficient. Our prior work, MetaOpt, shows many of the ...

Identified and explained in detail the gaps and possible future works for improvement in two popular research papers that used heuristic and meta-heuristic algorithms to solve multi-objective vehicle ...

Abstract: Transformers are critical components in electrical power systems, enabling efficient voltage regulation and energy transmission. Their design involves complex trade-offs among electrical, ...

A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and more useful. PROVIDENCE, R.I. [Brown University] — With the rise of 3D ...

Heuristic designing is a practical and indispensable tool leveraged in standard fields like artificial intelligence and operations research to find satisfactory solutions to complex optimisation ...

Active learning enables prediction models to achieve better performance faster by adaptively querying an oracle for the labels of data points. Sometimes the oracle is a human, for example when a ...

ABSTRACT: This study presents a two-echelon inventory routing problem (2E-IRP) with an end-of-tour replenishment (ETR) policy whose distribution network consists of a supplier, several distribution ...

Abstract: Automatic algorithm design has gained extensive research interest in addressing combinatorial optimization problems (COPs). Neural Combinatorial Optimization (NCO) is a novel application of ...