Parallel genetic algorithms (PGAs) have been developed to reduce the large execution times that are associated with serial genetic algorithms (SGAs). They have also been used to s...
Lee Wang, Anthony A. Maciejewski, Howard Jay Siege...
This paper studies the multi-objectivization of single-objective optimization problems (SOOP) using evolutionary multi-objective algorithms (EMOAs). In contrast to the single-obje...
We present a hybrid Genetic Algorithm that incorporates the Generalized Partition Crossover (GPX) operator to produce an algorithm that is competitive with the state of the art for...
Abstract- Simulated annealing (SA) is an effective general heuristic method for solving many combinatorial optimization problems. This paper deals with two problems in SA. One is ...
There are two reasons for parallelizing a metaheuristic if one is interested in performance: (i) given a fixed time to search, the aim is to increase the quality of the solutions f...