Elite Artificial Bee Colony for Makespan Optimisation in Job Shop with Interval Uncertainty

  1. Hernán Díaz 1
  2. Juan José Palacios 1
  3. Inés González-Rodríguez 2
  4. Camino R. Vela 1
  1. 1 University of Oviedo, Gijón, Spain
  2. 2 Universidad de Cantabria, Santander, Spain
Libro:
Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence: 9th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2022, Puerto de la Cruz, Tenerife, Spain, May 31 – June 3, 2022, Proceedings, Part II
  1. José Manuel Ferrández Vicente (dir. congr.)
  2. José Ramón Alvarez Sánchez (dir. congr.)
  3. Félix de la Paz López (dir. congr.)
  4. Hojjat Adeli

Editorial: Springer Suiza

ISBN: 978-3-031-06527-9

Año de publicación: 2022

Páginas: 98-108

Tipo: Capítulo de Libro

DIALNET GOOGLE SCHOLAR

Resumen

This paper addresses a variant of the Job Shop Scheduling Problem with makespan minimisation where uncertainty in task durations is taken into account and modelled with intervals. Given the problem’s complexity, we tackle it using a metaheuristic approach. Specifically, we propose a novel Artificial Bee Colony algorithm incorporating three different selection mechanisms that help in guiding the search towards more promising areas. A parametric analysis is conducted and a comparison of the different selection strategies is performed on a set of benchmark instances. The results illustrate the benefit of using the new guiding strategies, improving the behaviour of the ABC algorithm, which compares favourably to the state-of-the art in the problem. An additional study is conducted to assess the robustness of the solutions obtained under each guiding strategy.

Fuente de los datos: Dialnet