Speci cation re nement is part of formal program derivation a method by which software is directly constructed from a provably correct speci cation Because program derivation is an intensive manual exercise used for critical software systems an automated approach would allow it to be viable for many other types of software systems The goal of this research is to de termine if genetic programmin...

The aim of this chapter is to investigate whether Genetic Programming (GP) can be used as a nature inspired human competitive solution for producing machine. A primary goal of machine learning strategies is to allow the user to state a problem in as high a level as possible and provide a solution without further human intervention. While we are still some way off this goal, GP has proven itself...

Speciication reenement is part of formal program derivation, a method by which software is directly constructed from a provably correct spe-ciication. Because program derivation is an intensive manual exercise used for critical software systems, an automated approach would allow it to be viable for many other types of software systems. The goal of this research is to determine if genetic progra...

the problem of staff scheduling at a truck hub for loading and stripping of the trucks is an important and difficult problem to optimize the labor efficiency and cost. the trucks enter the hub at different hours a day, in different known time schedules and operating hours. in this paper, we propose a goal programming to maximize the labor efficiency via minimizing the allocation cost. the propo...

We describe the programming system for the graph-transformation language GP, focusing on the implementation of its compiler and abstract machine. We also compare the system’s performance with other graph-transformation systems. The GP language is based on conditional rule schemata and comes with a simple formal semantics which maps input graphs to sets of output graphs. The implementation faith...

The relationship between generalization and solutions functional complexity in genetic programming (GP) has been recently investigated. Three main contributions are contained in this paper: (1) a new measure of functional complexity for GP solutions, called Graph Based Complexity (GBC) is defined and we show that it has a higher correlation with GP performance on out-of-sample data than another...

abstract it is the purpose of this article to introduce a linear approximation technique for solving a fractional chance constrained programming (cc) problem. for this purpose, a fuzzy goal programming model of the equivalent deterministic form of the fractional chance constrained programming is provided and then the process of defuzzification and linearization of the problem is started. a samp...