Cam shape optimization by genetic algorithm. (English) Zbl 1058.68114
Acta Wasaensia 70, Computer Science 2. Vaasa: Universitas Wasaensis (Diss.) (ISBN 951-683-801-4/pbk). 247 p. (1999).
This book presents a University thesis at the University of Vaasa, Finland, on a genetic algorithm for the cam shape design problem in mechanical engineering.
The first chapter presents an introduction to the problem of cam design, which translates to a 2-dimensional free form boundary shape optimization problem. The problem is a multi-objective, multi-constrained problem with about 20–40 design variables. The general principles of genetic optimization and evolutionary algorithms are also presented in this chapter.
The second and third chapters present in detail the formulation of the research problem and solution. In chapter 5, the problem is extended to the problem of optimization of a diesel fuel injection cam, again using a genetic approach.
In chapter 6, a distributed version of the algorithm is presented, where the problem is split into several computer workstations which work in parallel, thus speeding up the solution time (a master-slave model).
The last part of the thesis concentrates on generalized approaches to cam shape optimization using evolutionary algorithms. The thesis concludes with a section on conclusions and recommendations for future work, as well as Annexes with some of the Fortran subroutines used.
The first chapter presents an introduction to the problem of cam design, which translates to a 2-dimensional free form boundary shape optimization problem. The problem is a multi-objective, multi-constrained problem with about 20–40 design variables. The general principles of genetic optimization and evolutionary algorithms are also presented in this chapter.
The second and third chapters present in detail the formulation of the research problem and solution. In chapter 5, the problem is extended to the problem of optimization of a diesel fuel injection cam, again using a genetic approach.
In chapter 6, a distributed version of the algorithm is presented, where the problem is split into several computer workstations which work in parallel, thus speeding up the solution time (a master-slave model).
The last part of the thesis concentrates on generalized approaches to cam shape optimization using evolutionary algorithms. The thesis concludes with a section on conclusions and recommendations for future work, as well as Annexes with some of the Fortran subroutines used.
Reviewer: Efstratios Rappos (London)
MSC:
68U07 | Computer science aspects of computer-aided design |
68U20 | Simulation (MSC2010) |
68W15 | Distributed algorithms |
90C59 | Approximation methods and heuristics in mathematical programming |
68-01 | Introductory exposition (textbooks, tutorial papers, etc.) pertaining to computer science |
68T05 | Learning and adaptive systems in artificial intelligence |
68T10 | Pattern recognition, speech recognition |