in this paper the real-world occurrence of the multiple-product multiple-constraint single period newsboy problem with two objectives, in which there is incremental discounts on the purchasing prices, is investigated. the constraints are the warehouse capacity and the batch forms of the order placements. the first objective of this problem is to find the order quantities such that the expected ...

This paper studies Genetic Programming (GP) and its relation to the Genetic Algorithm (GA). GP uses a GA approach to breed successive populations of programs, represented in the chromosomes as parse trees, until a program that solves the problem emerges. However, parse trees are not naturally homologous, consequently changes had to be introduced into GP. To better understand these changes it wo...

One of the most general forms of representing and specifying behavior is by using a computer language. We have evaluated the use of the evolutionary technique of Genetic Programming (GP) to directly control a miniature robot. The goal of the GP-system was to evolve real-time obstacle avoiding behavior from sensorial. The evolved programs are used in a sense-think-act context. We employed a nove...

the present study aims to provide a solution to optimize land use through multi-objective linear programming, and to solve the conflicts generated in the process using game theory, in two cities of gorgan and kurdkoy, iran. the primary land use planning was completed for seven land use through multi-criteria evaluation and then a first allocation was implanted using mola. in the secondary land ...

Genetic Programming is a method for evolving functions that find approximate or exact solutions to problems. There are many problems that traditional Genetic Programming (GP) cannot solve, due to the theoretical limitations of its paradigm. A Turing machine (TM) is a theoretical abstraction that express the extent of the computational power of algorithms. Any system that is Turing complete is s...

Multiple loop circuits interconnect the basal ganglia and the frontal cortex, and each part of the cortico-basal ganglia loops plays an essential role in neuronal computational processes underlying motor behavior. To gain deeper insight into specific functions played by each component of the loops, we compared response properties of neurons in the globus pallidus (GP) with those in the dorsal p...

The aim of inductive machine learning (ML) is to generate models that can make predictions from analysis of data sets. These data sets consist of a number of instances or examples, each example described by a set of attributes. It is known that the quality or relevance of the attributes of a data set is a key issue when trying to obtain models with a satisfactory level of generalization. There ...

We extend our analysis of repetitive patterns found in genetic programming genomes to tree based GP. As in linear GP, repetitive patterns are present in large numbers. Size fair crossover limits bloat in automatic programming, preventing the evolution of recurring motifs. We examine these complex properties in detail: e.g. using depth v. size Catalan binary tree shape plots, subgraph and subtre...