Parallel genetic algorithms for product configuration management on PC cluster systems

This work presents two parallel genetic algorithms (PGAs) for product configuration management: a parallel conventional genetic algorithm (PCGA) and a parallel multiple-searching genetic algorithm (PMGA). This parallel/distributed approach is based on a coarse-grained (or island) paradigm which is implemented on a cluster of PCs using message passing interface for the genetic information interchange. The product configuration problem assuming that customers would like to have minimum cost and a customized product can be obtained by finding the shortest path of the configuration network diagram. The performance of these algorithms is estimated by comparing the solutions of PGAs with those of sequential genetic algorithms (GAs) and mathematical programming. A weighting scale example from an empirical study is reported for illustrational purposes. Computational results show that the solutions obtained from the PMGA outperform other GAs in both accuracy and efficiency.

[1]  Michael Allen,et al.  Parallel programming: techniques and applications using networked workstations and parallel computers , 1998 .

[2]  Dalila Megherbi,et al.  Implementation of a parallel Genetic Algorithm on a cluster of workstations: Traveling Salesman Problem, a case study , 2001, Future Gener. Comput. Syst..

[3]  Enrique Alba,et al.  Heterogeneous Computing and Parallel Genetic Algorithms , 2002, J. Parallel Distributed Comput..

[4]  S. Mirzaei,et al.  Validation of a parallel genetic algorithm for image reconstruction from projections , 2003, J. Parallel Distributed Comput..

[5]  Injun Choi,et al.  An Architecture for Active Product Configuration Management in Industrial Virtual Enterprises , 2001 .

[6]  Cheng-Fa Tsai,et al.  A Multiple-Searching Approach to Genetic Algorithms for Solving Traveling Salesman Problem , 2002, JCIS.

[7]  Yoshikazu Fukuyama,et al.  Parallel genetic algorithm for generation expansion planning , 1996 .

[8]  Chae Y. Lee,et al.  Parallel genetic algorithms for the earliness-tardiness job scheduling problem with general penalty weights , 1995 .

[9]  Carsten Svensson,et al.  Limits and opportunities in mass customization for "build to order" SMEs , 2002, Comput. Ind..

[10]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[11]  Tomoyuki Hiroyasu,et al.  The differences of parallel efficiency between the two models of parallel genetic algorithms on PC cluster systems , 2000, Proceedings Fourth International Conference/Exhibition on High Performance Computing in the Asia-Pacific Region.

[12]  Shlomo Globerson,et al.  Discrepancies between customer expectations and product configuration , 1997 .

[13]  G. Parry,et al.  Build to Order: The Road to the 5-Day Car , 2008 .

[14]  C. Forza,et al.  Managing for variety in the order acquisition and fulfilment process: The contribution of product configuration systems , 2002 .

[15]  Li-Chieh Chen,et al.  Optimization of product configuration design using functional requirements and constraints , 2002 .

[16]  Mitchell M. Tseng,et al.  Fundamentals of product family architecture , 2000 .

[17]  Dalessandro Soares Vianna,et al.  A parallel evolutionary algorithm for the vehicle routing problem with heterogeneous fleet , 1998, Future Gener. Comput. Syst..

[18]  Juan Liu,et al.  Selecting informative genes with parallel genetic algorithms in tissue classification. , 2001, Genome informatics. International Conference on Genome Informatics.

[19]  Randy L. Haupt,et al.  Practical Genetic Algorithms , 1998 .

[20]  Virginia E. Barker,et al.  Expert systems for configuration at Digital: XCON and beyond , 1989, Commun. ACM.

[21]  Fabrizio Salvador,et al.  Product configuration and inter-firm co-ordination: an innovative solution from a small manufacturing enterprise , 2002, Comput. Ind..

[22]  Mauricio Solar,et al.  A parallel genetic algorithm to solve the set-covering problem , 2002, Comput. Oper. Res..

[23]  Ping Yi Chao,et al.  Analysis of assembly through product configuration , 2001 .

[24]  Dalessandro Soares Vianna,et al.  An asynchronous parallel metaheuristic for the period vehicle routing problem , 2001, Future Gener. Comput. Syst..

[25]  David E. Goldberg,et al.  Efficient Parallel Genetic Algorithms: Theory and Practice , 2000 .

[26]  Melanie Mitchell,et al.  An introduction to genetic algorithms , 1996 .

[27]  Robert E. Young,et al.  Configuring computer systems through constraint-based modeling and interactive constraint satisfaction , 1995 .