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...
We present an "adaptive multi-start" genetic algorithm for the Euclidean traveling salesman problem that uses a population of tours locally optimized by the Lin-Kernigha...
Dan Bonachea, Eugene Ingerman, Joshua Levy, Scott ...
— For complex optimization problems, several population-based heuristics like Multi-Objective Evolutionary Algorithms have been developed. These algorithms are aiming to deliver ...
— A number of multi-objective genetic algorithms (MOGAs) have been developed to obtain Pareto optimal solutions for multi-objective optimization problems. However, as these metho...
We introduce a general and in a certain sense time-optimal way of solving one problem after another, efficiently searching the space of programs that compute solution candidates, i...