A genetic algorithm that generates and evaluates assembly plans is proposed This algorithm is able to generate near-optimal assembly plans through purposely developed crossover and mutation operators starting from a randomly initialized population of assembly sequences. The optimization criteria we used to assess the quality of feasible assembly sequences are: i) to minimize the orientation changes of the product; ii) to minimize the gripper changes, and iii) to group as much as possible technologically similar assembly operations. Experimental results that confirm the validity of our approach are also included.

Assembly planning based on genetic algorithms

LAZZERINI, BEATRICE;MARCELLONI, FRANCESCO;DINI, GINO;FAILLI, FRANCO
1999-01-01

Abstract

A genetic algorithm that generates and evaluates assembly plans is proposed This algorithm is able to generate near-optimal assembly plans through purposely developed crossover and mutation operators starting from a randomly initialized population of assembly sequences. The optimization criteria we used to assess the quality of feasible assembly sequences are: i) to minimize the orientation changes of the product; ii) to minimize the gripper changes, and iii) to group as much as possible technologically similar assembly operations. Experimental results that confirm the validity of our approach are also included.
1999
0780352114
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/194255
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 16
  • ???jsp.display-item.citation.isi??? 9
social impact