This paper describes a genetic algorithm (GA) based application for computer aided design and optimisation of cam shapes used on internal-combustion engine camshafts. A shape optimisation of cam cross-section is a multiobjective optimisation problem of two-dimensional geometric shape in a heavily constrained environment. By representing the cam shape in parametric form, the shape optimisation problem is converted to a parameter optimisation problem.

A cam shape is parametrized using 6th order splines. The real valued control points of those splines are used as a chromosomes of a real coded genetic algorithm. Each individual of the population consists of a set of 28 floating point values which unambiguously describes a cam shape. Thus, the individuals of the population are actually the alternative cam shape designs in a parametric form.

The fitness function of the genetic algorithm is based on evaluation of a simulated cam mechanism model.

This paper focuses on possibilities to implement parallelly or/and distributedly this kind of shape optimisation system in order to speed up the time consuming optimisation process. A distributed computation method in a local area network (LAN) is proposed.

The method is based on a population maintained by a master process. Evaluation of fitness values is distributed via a local area network to slave processes which work partially asynchronously with respect to the main process. The number of slave processes can be freely selected and also freely altered during the optimisation process. Shared disk files are used as a logical interface between master and slave processes.

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