This paper discusses a parallel genetic algorithm (PGA) which focuses on the local operator for Traveling salesman problem (TSP). The local operator is a simple GA named as Local Genetic Algorithm (LGA). The LGA is combined to another GA named as Global Genetic Algorithm (GGA). It increases the computational time running a GA as a local operator in another one. To solve this problem, we build a...

Linkage identification algorithms identify linkage groups — sets of loci tightly linked — before genetic optimizations for their recombination operators to work effectively and reliably. This paper proposes a parallel genetic algorithm (GA) based on the linkage identification algorithm and shows its effectiveness compared with other conventional parallel GAs such as master-slave and island mode...

this paper presents the results of a comprehensive study on the efficiency of planar parallel mechanisms, considering their kinetostatic performance and also, their workspace. this aim is approached upon proceeding single- and multi-objective optimization procedures. kinetostatic performances of ten different planar parallel mechanisms are analyzed by resorting to a recent index, kinematic sens...

Many optimization problems have complex search space, which either increase the solving problem time or finish searching without obtaining the best solution. Genetic Algorithm (GA) is an optimization technique used in solving many practical problems in science, engineering, and business domains. Parallel Genetic Algorithm (PGA) has been widely used to increase speed of GA, especially after the ...

Proper arrangement of facility layout is a key issue in management that influences efficiency and the profitability of the manufacturing systems. Parallel Row Ordering Problem (PROP) is a special case of facility layout problem and consists of looking for the best location of n facilities while similar facilities (facilities which has some characteristics in common) should be arranged in a row ...

This paper studies the parallel machine scheduling problem subject to machine and job deterioration in a batched delivery system. By the machine deterioration effect, we mean that each machine deteriorates over time, at a different rate. Moreover, job processing times are increasing functions of their starting times and follow a simple linear deterioration. The objective functions are minimizin...

Current genetic algorithm require both management of huge amounts of data and heavy computation, fulfilling these requirements calls for simple ways to implement parallel computing. In this paper, serial genetic algorithm was designed to parallel GA; this technology appears to be particularly well adapted to this task. Here we introduce two related mechanism: elite reserve strategy and MPI. The...

This paper surveys a number of parallelization techniques for genetic algorithms, focusing on two: the distributed genetic algorithm and the distributed tness computation. While parallelization of serial algorithms usually requires certain amount of tricks and twitches, the genetic algorithms are parallel by their nature. This feature of genetic algorithms is widely exploited and there exists a...

A hybrid algoritm to find the absolute extreme point of a multimodal scalar function of many variables is presented. The algorithm is well suited to be implemeted in parallel over a distributed computer environment. The algorithm is suitable when the objective function is expensive to compute, the computation can be affected by noise and/or partial derivatives cannot be calculated. The method u...

introduction: raman spectroscopy, that is a spectroscopic technique based on inelastic scattering of monochromatic light, can provide valuable information about molecular vibrations, so using this technique we can study molecular changes in a sample. material and methods: in this research, 153 raman spectra obtained from normal and dried skin samples. baseline and electrical noise were eliminat...