The maximum weight clique problem (MWCP) is an important generalization of the
maximum clique problem with wide applications. In this study, we develop two efficient local …

This paper introduces an enhanced meta-heuristic (ML-ACO) that combines machine
learning (ML) and ant colony optimization (ACO) to solve combinatorial optimization …

In this article, we investigate problem reduction techniques using stochastic sampling and
machine learning to tackle large-scale optimization problems. These techniques …

This paper proposes an iterated local search (ILS) based heuristic for the weighted vertex
coloring problem (WVCP). Given a graph G (V, E) with a weight w (v) associated with each …

Given a graph G (V, E) and a value s ∈ N s∈ N, an s-plex S is a subset of V such that each
vertex v ∈ S v∈ S has at least| S|-s| S|-s adjacent vertices in the subgraph induced by S …

This study proposes a new parallel local search algorithm (Par-LS) for solving the maximum
vertex weight clique problem (MVWCP) in large graphs. Solving the MVWCP in a large …

This paper presents a CUDA/C++ library, called GPU-BRKGA, for accelerating the biased
random-key genetic algorithm (BRKGA). Our library features an easy to use API that allows …

Diversified top-k weight clique (DTKWC) search problem is an important generalization of
the diversified top-k clique (DTKC) search problem with practical applications. The …

This book is related to the educational networking (EN) domain, an incipient but disrupting
trend engaged in extending and improving formal and informal academic practices by …

The maximum diversity problem (MDP), a widely studied combinatorial optimization problem
due to its broad applications, has seen numerous heuristic methods proposed. However …