Selection and Optimization of Alternative Modular Products Using Evolutionary Computing

Durán O.; Rodríguez N.; Perez, L.

Abstract

In most configurations of modular structures, products are assumed to have a unique modular structure. However, it is well known that alternatives for constructing modular structures may exist in any level of abstraction. Explicit considerations of alternative structures invoke changes in the number of module instances so that lower costs, more independency of structures and higher efficiency can be achieved. Relatively few research papers deal with the optimization of modular structures problem with alternative assembly combinations aiming at minimization of module investments was found in the literature. A genetic algorithm (GA) was applied to solve the optimization problem of selecting and combining the alternative of modular structures to create a set of modular structures minimizing the cost involved in its implementation. Test results are presented and the performance of the proposed GA and compared to Simulated Annealing technique and compared to solutions obtained from total enumeration tests. Finally an evaluation of the performance of the proposed G.A. in a set of large problems is presented and discussed. © 2009 Springer-Verlag Berlin Heidelberg.

Más información

Título según WOS: Selection and Optimization of Alternative Modular Products Using Evolutionary Computing
Título según SCOPUS: Selection and optimization of alternative modular products using evolutionary computing
Título de la Revista: ELECTRONIC GOVERNANCE WITH EMERGING TECHNOLOGIES, EGETC 2022
Volumen: 65
Editorial: SPRINGER INTERNATIONAL PUBLISHING AG
Fecha de publicación: 2009
Página de inicio: 35
Página final: 46
Idioma: English
DOI:

10.1007/978-3-642-10741-2_5

Notas: ISI, SCOPUS