Parallel cooperative optimization through hyperheuristics

OTEIZA P.P.; RODRIGUEZ D.A.; BRIGNOLE N.B.

Computer-Aided Chemical Engineering: 13th International Symposium On Process Systems Engineering PSE 2018

Elsevier

Lugar: Amsterdam; Año: 2018; p. 805 - 810

A hyperheuristics that coordinates the interaction between various metaheuristic techniques is presented. The proposed algorithm, which we called Parallel Optimizer With Hyperheuristics (POWH), includes a Genetic Algorithm, Simulated Annealing, and Ant Colony Optimization. In view of the need to escape from local optima, information exchanges take place between these metaheuristics. In this way, it is possible to take advantage of each metaheuristic? particular strengths during the search process. Testing related to the hyperheuristic approach was carried out by using the following real-life case studies: I. the optimal design of a subsea pipeline network and II. the urban bus-transit optimal planning. In both cases, a satisfactory reduction of the computational time was achieved due to the parallel implementation that allowed several metaheuristics to run simultaneously. Moreover, better results were obtained thanks to the parallel cooperative combination of metaheuristics in comparison with the serial execution of any individual technique.