Scatter Search

Scatter search This chapter discusses the principles and foundations behind scatter search and its application to the problem of training neural networks. Scatter search is an evolutionary method that has been successfully applied to a wide array of hard optimization problems. Scatter search constructs new trial solutions by combining so-called reference solutions and employing strategic designs that exploit context knowledge. In contrast to other evolutionary methods like genetic algorithms, scatter search is founded on the premise that systematic designs and methods for creating new solutions afford significant benefits beyond those derived from recourse to randomization. Our implementation goal is to create a combination of the five elements in the scatter search methodology that proves effective when searching for optimal weight values in a multilayer neural network. Through experimentation, we show that our instantiation of scatter search can compete with the best-known training algorithms in terms of training quality while keeping the computational effort at a reasonable level. (Source:

References in zbMATH (referenced in 224 articles , 1 standard article )

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  1. Amaran, Satyajith; Sahinidis, Nikolaos V.; Sharda, Bikram; Bury, Scott J.: Simulation optimization: a review of algorithms and applications (2016)
  2. Cordeiro, Gauss M.; Lima, Maria do Carmo S.; Gomes, Antonio E.; da-Silva, Cibele Q.; Ortega, Edwin M.M.: The gamma extended Weibull distribution (2016)
  3. Glover, Fred; Hao, Jin-Kao: $f$-flip strategies for unconstrained binary quadratic programming (2016)
  4. Khalid, Ruzelan; Nawawi, Mohd.Kamal Mohd.; Kawsar, Luthful A.; Ghani, Noraida A.; Kamil, Anton A.; Mustafa, Adli: The evaluation of pedestrians’ behavior using $M/G/C/C$ analytical, weighted distance and real distance simulation models (2016)
  5. Yang, Zhaoyang; Zhang, Guojun; Zhu, Haiping: Multi-neighborhood based path relinking for two-sided assembly line balancing problem (2016)
  6. Basu, Sumanta; Sharma, Megha; Ghosh, Partha Sarathi: Metaheuristic applications on discrete facility location problems: a survey (2015)
  7. Camacho-Vallejo, José-Fernando; Muñoz-Sánchez, Rafael; González-Velarde, José Luis: A heuristic algorithm for a supply chain’s production-distribution planning (2015)
  8. Gevezes, Theodoros; Pitsoulis, Leonidas: A greedy randomized adaptive search procedure with path relinking for the shortest superstring problem (2015)
  9. González, Miguel A.; Oddi, Angelo; Rasconi, Riccardo; Varela, Ramiro: Scatter search with path relinking for the job shop with time lags and setup times (2015)
  10. Hiermann, Gerhard; Prandtstetter, Matthias; Rendl, Andrea; Puchinger, Jakob; Raidl, Günther R.: Metaheuristics for solving a multimodal home-healthcare scheduling problem (2015)
  11. Ivorra, Benjamin; Mohammadi, Bijan; Manuel Ramos, Angel: A multi-layer line search method to improve the initialization of optimization algorithms (2015)
  12. Martí, Rafael; Corberán, Ángel; Peiró, Juanjo: Scatter search for an uncapacitated $p$-hub median problem (2015)
  13. Qi, Jian-Jun; Liu, Ya-Jie; Jiang, Ping; Guo, Bo: Schedule generation scheme for solving multi-mode resource availability cost problem by modified particle swarm optimization (2015)
  14. Shylo, V.P.; Glover, F.; Sergienko, I.V.: Teams of global equilibrium search algorithms for solving the weighted maximum cut problem in parallel (2015)
  15. Terán-Villanueva, J.David; Fraire Huacuja, Héctor Joaquín; Carpio Valadez, Juan Martín; Pazos Rangel, Rodolfo; Puga Soberanes, Héctor José; Martínez Flores, José A.: A heterogeneous cellular processing algorithm for minimizing the power consumption in wireless communications systems (2015)
  16. Yaghini, Masoud; Karimi, Mohammad; Rahbar, Mohadeseh: A set covering approach for multi-depot train driver scheduling (2015)
  17. Amaran, Satyajith; Sahinidis, Nikolaos V.; Sharda, Bikram; Bury, Scott J.: Simulation optimization: a review of algorithms and applications (2014)
  18. Benavides, Alexander J.; Ritt, Marcus; Miralles, Cristóbal: Flow shop scheduling with heterogeneous workers (2014)
  19. De Freitas, Alan Robert Resende; Guimarães, Frederico Gadelha; Silva, Rodrigo César Pedrosa; Souza, Marcone Jamilson Freitas: Memetic self-adaptive evolution strategies applied to the maximum diversity problem (2014)
  20. Jaradat, Ghaith; Ayob, Masri; Ahmad, Zulkifli: On the performance of scatter search for post-enrolment course timetabling problems (2014)

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