Abstract The performance of Genetic Algorithm (GA) depends on various operators.
Crossover operator is one of them. Crossover operators are mainly classified as application …

“Exploration and exploitation are the two cornerstones of problem solving by search.” For
more than a decade, Eiben and Schippers' advocacy for balancing between these two …

Sensor networks have a lot of applications such as battlefield surveillance, environmental
monitoring, and industrial diagnostics. Coverage is one of the most important performance …

Most textbooks on modern heuristics provide the reader with detailed descriptions of the
functionality of single examples like genetic algorithms, genetic programming, tabu search …

Genetic algorithms (GA) are stimulated by population genetics and evolution at the
population level where crossover and mutation comes from random variables. The problems …

Evolutionary algorithms are bio-inspired algorithms based on Darwin's theory of evolution.
They are expected to provide non-optimal but good quality solutions to problems whose …

The max-cut problem is one of well-known NP-complete problems and has applications in
various fields such as the design process for VLSI (Very-Large-Scale Integration) chips and …

The graph partitioning problem occurs in numerous applications such as circuit placement,
matrix factorization, load balancing, and community detection. For this problem, genetic …

Graphs are used for modeling a large spectrum of data from the web, to social connections
between individuals, to concept maps and ontologies. As the number and complexities of …

The present invention discloses a method for combinatorial layout design, in particular
family mold layout design, using a computer. The method starts with receiving design …