A local‐search heuristic for finding high‐quality solutions for many hard optimization
problems is explored. The method is inspired by recent progress in understanding far‐from …

While Boolean logic has been the backbone of digital information processing, there exist
classes of computationally hard problems wherein this paradigm is fundamentally inefficient …

Deep learning has consistently defied state-of-the-art techniques in many fields over the last
decade. However, we are just beginning to understand the capabilities of neural learning in …

We study the graph coloring problem over random graphs of finite average connectivity c.
Given a number q of available colors, we find that graphs with low connectivity admit almost …

Colouring of fuzzy graphs has several applications in real world. In this paper, a new
concept of colouring of fuzzy graphs has been introduced. Also, some important terms like …

We study the impact of backbones in optimization and approximation problems. We show
that some optimization problems like graph coloring resemble decision problems, with …

Phase transitions play an important role in understanding search difficulty in combinatorial
optimisation. However, previous attempts have not revealed a clear link between fitness …

Graph vertex coloring with a given number of colors is a well-known and much-studied NP-
complete problem. The most effective methods to solve this problem are proved to be hybrid …

A recently introduced general-purpose heuristic for finding high-quality solutions for many
hard optimization problems is reviewed. The method is inspired by recent progress in …

This paper carries out a comparison of the fitness landscape for four classic optimization
problems: Max-Sat, graph-coloring, traveling salesman, and quadratic assignment. We have …