Abstract Due to the shortcomings of GA in path planning, there are too many control variables and it is easy fall into local areas. We introduce idea a gene bank store new chromosomes generated each time bank. The linear regression proposed predict probability crossover mutation next generation. At same time, method increasing chromosome diversity proposed, which avoids problem that difficult s...

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...

in this study, a cross-docking system is designed at strategic and tactical levels. for making the strategic decisions, a multi-objective nonlinear location allocation model for cross-docks is presented based on a distri-bution location allocation model by andreas klose and andreas drexl. the model is further developed to in-clude the whole supply chain members and the objective functions are w...

This document describes picoGA, our submission to the Tiny GA programming competition at GECCO 2006. picoGA is optimized to have small code size and a small memory footprint. It is implemented in the Matlab programming language. Matlab is an interpretted language that is optimized for performing operations on arrays. Loops, especially nested loops, tend to run slowly in Matlab. It is possible h...

Investor decision making has always been affected by two factors: risk and returns. Considering risk, the investor expects an acceptable return on the investment decision horizon. Accordingly, defining goals and constraints for each investor can have unique prioritization. This paper develops several approaches to multi criteria portfolio optimization. The maximization of stock returns, the pow...

The paper deals with efficiency comparison of two global evolutionary optimization methods implemented in MATLAB. Attention is turned to an elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel multi-objective Particle Swarm Optimization (PSO). The performance of optimizers is compared on three different test functions and on a cavity resonator synthesis. The microwave resonator...

this study emphasized the ability of genetic algorithm and cellular automate to simulate urban land use changes by integrating adaptive model. the most important part of modeling is to define transition rules.  in this research, a cellular automata model in dinamica ego software was used coupled with genetic algorithm. according to disability of the software for manipulating large number of var...

in this paper, the distribution network for multi-level supply chain has been studied. products produced in factories are sent to customers through warehouses and distribution centers based on specific demands. warehouses as holding inventory facilities are located close to factories and the distribution centers are placed in the most accessible locations for services near customers. each item ...