This paper deals with a new approach for solving fuzzy differential equations based on genetic programming. This method produces some trial solutions and seeks the best of them. If the solution cannot be expressed in a closed analytical form then our method produces an approximation with a controlled level of accuracy. Furthermore, the numerical results reveal the potential of the proposed appr...

We present the application of Genetic Programming (GP) in Branch and Bound (B&B) based Mixed Integer Linear Programming (MIP). The hybrid architecture introduced employs GP as a node selection expression generator: a GP run, embedded into the B&B process, exploits the characteristics of the particular MIP problem being solved, evolving a problem-specific node selection method. The evolved metho...

this paper investigates the problem of selecting and scheduling a set of projects among available projects. each project consists of several tasks and to perform each one some resource is required. the objective is to maximize total benefit. the paper constructs a mathematical formulation in form of mixed integer linear programming model. three effective metaheuristics in form of the imperialis...

the problem of lot sizing, sequencing and scheduling multiple products in flow line production systems has been studied by several authors. almost all of the researches in this area assumed that setup times and costs are sequence –independent even though sequence dependent setups are common in practice. in this paper we present a new mixed integer non linear program (minlp) and a heuristic meth...

in this paper, the capacitated location-routing problem with fuzzy demands (clrp-fd) is considered. the clrp-fd is composed of two well-known problems: facility location problem and vehicle routing problem. the problem has many real-life applications of which some have been addressed in the literature such as management of hazardous wastes and food and drink distribution. in clrp-fd, a set of c...

in this paper, a mathematical modeling is developed for plastic analysis of planar frames. to this end, the researcher tried to design an optimization model in linear format in order to solve large scale samples. the computational result of cpu time requirement is shown for different samples to prove efficiency of this method for large scale models. the fundamental concept of this model is obta...

In this paper we propose the framework for a grammar-guided genetic programming system called Tree-Adjunct Grammar Guided Genetic Programming (TAGGGP). Some intuitively promising aspects of the model compared with other grammar-guided evolutionary methods are also highlighted. 1 Introduction Genetic programming (GP) is considered to be a machine learning method, which induces a population of co...