Genetic Programming (GP) has been shown to be a good method of predicting functions. In this context, a solution given by GP generally consists of a sole predictor. In contrast, Stack-based GP systems manipulate structures containing several predictors, which can be considered as teams of predictors. Work in Machine Learning reports that combining predictors gives good results in terms of both ...

This paper deals with the development and analysis of an efficient, evolutionary, intelligent, data-based, mathematical modelling method for complex non-linear systems. A new hybrid evolutionary method using genetic programming (GP) and evolutionary programming approaches is proposed. The potentials of the hybrid method for modelling complex, dynamic systems including single and two-link terres...

this study provides an alternative approach to decisionmaking and its application in selecting the best attack helicopter. in thisway, principal component analysis (pca) is used to find the weights ofthe criteria after identifying the effective criteria for the evaluation andselection of attack helicopters. these weights, then, applied in theobjective function of goal programming (gp) model. fi...

This paper presents a genetic programming (GP) approach to extract symbolic rules from data sets with continuous-valued classes, called GPMCC. The GPMCC makes use of a genetic algorithm (GA) to evolve multi-variate non-linear models [Potgieter, G., & Engelbrecht, A. (2007). Genetic algorithms for the structural optimisation of learned polynomial expressions. Applied Mathematics and Computation]...

One of the mayor problems of programming a cruise circuit is to decide which destinations to include and which don’t. Thus a decision problem emerges, that might be solved using a linear and goal programming approach. The problem becomes more complex if several boats in the fleet must be programmed in a limited schedule, trying their capacity matches best a seasonal demand and also attempting t...

This paper describes Postfix-GP system, postfix notation based Genetic Programming (GP), for solving symbolic regression problems. It presents an object-oriented architecture of Postfix-GP framework. It assists the user in understanding of the implementation details of various components of Postfix-GP. Postfix-GP provides graphical user interface which allows user to configure the experiment, t...

We describe a design problem arising in the colour printing industry and discuss a number of integer linear programming and constraint programming approaches to its solution. Despite the apparent simplicity of the problem it presents a challenge for both approaches. We present results for three typical cases and show that the constraint programming approach provides better results , although in...

Component-based Software Engineering (CBSE) and related technologies have demonstrated their strength in recent years by increasing development productivity and parts reuse. Recently, the Model Driven Architecture (MDA) has raised the abstraction level of programming languages to modeling languages that can be compiled by downward model transformations. Correspondingly, the goal of Generative P...

This paper proposes a bi-level linear programming problem with linear constraints, in which the linear objective functions are to be maximized with different rough goals, the suggested approach in this paper is mainly based on the iterative goal programming method of Dauer and Krueger to develop the optimal solution of the bi-level decisionmaker, then we uses the concepts of tolerance membershi...