Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …

Meta-heuristics are the most recent development in approximate search methods for solving
complex optimization problems, that arise in business, commerce, engineering, industry …

Systematic change of neighborhood within a possibly randomized local search algorithm
yields a simple and effective metaheuristic for combinatorial and global optimization, called …

Metaheuristics are the most exciting development in approximate optimization techniques of
the last two decades. They have had widespread successes in attacking a variety of difficult …

In this paper we examine a relatively unexplored approach to the design of heuristics, the
guided change of neighborhood in the search process. Using systematically this idea and …

Much work has been published on the theoretical aspects of simulated annealing. This
paper provides a brief overview of this theory and provides an introduction to the practical …

Abstract The recent Variable Neighborhood Search (VNS) metaheuristic combines local
search with systematic changes of neighborhood in the descent and escape from local …

Grey wolf optimizer (GWO) is known as one of the recent popular metaheuristic algorithms
inspired from the social collaboration and team hunting activities of grey wolves in nature …

Simulated Annealing, Its Variants and Engineering Applications Page 1 International Journal on
Artificial Intelligence Tools Vol. 25, No. 6 (2016) 1630001 (24 pages) c World Scientific …

In vehicle routing problems with time windows (VRPTW), a set of vehicles with limits on
capacity and travel time are available to service a set of customers with demands and …