Memetic and Opposition-Based Learning Genetic Algorithms for Sorting Unsigned Genomes by Translocations
نویسندگان
چکیده
A standard genetic algorithm for sorting unsigned genomes by translocations is improved in two different manners: 1. a memetic algorithm (GAMA ) is provided, which embeds a new stage of local search, based on the concept of mutation applied in only one gene; 2. an oppositionbased learning (GAOBL ) mechanism is provided, which explores the concept of internal opposition applied to a chromosome. The proposed approaches include a convergence control mechanism of the population using the Shannon entropy. Additionally, non-parametric statistical tests were performed to compare the proposed algorithms with the standard genetic algorithm. For the experiments, both biological and synthetic genomes were used. The results from these experiments showed that the GAMA outperforms the GAOBL and the genetic algorithm. The statistical tests confirmed these results showing that the GAMA has a better performance regarding the other algorithms.
منابع مشابه
A (1.408+ε)-Approximation Algorithm for Sorting Unsigned Genomes by Reciprocal Translocations
متن کامل
EMCSO: An Elitist Multi-Objective Cat Swarm Optimization
This paper introduces a novel multi-objective evolutionary algorithm based on cat swarm optimizationalgorithm (EMCSO) and its application to solve a multi-objective knapsack problem. The multi-objective optimizers try to find the closest solutions to true Pareto front (POF) where it will be achieved by finding the less-crowded non-dominated solutions. The proposed method applies cat swarm optim...
متن کاملGenetic and Memetic Algorithms for Sequencing a New JIT Mixed-Model Assembly Line
This paper presents a new mathematical programming model for the bi-criteria mixed-model assembly line balancing problem in a just-in-time (JIT) production system. There is a set of criteria to judge sequences of the product mix in terms of the effective utilization of the system. The primary goal of this model is to minimize the setup cost and the stoppage assembly line cost, simultaneously. B...
متن کاملEstimating Genome Reversal Distance by Genetic Algorithm
Sorting by reversals is an important problem in inferring the evolutionary relationship between two genomes. The problem of sorting unsigned permutation has been proven to be NP-hard. The best guaranteed error bounded is the 3/2approximation algorithm. However, the problem of sorting signed permutation can be solved easily. Fast algorithms have been developed both for finding the sorting sequen...
متن کاملSOLVING A STEP FIXED CHARGE TRANSPORTATION PROBLEM BY A SPANNING TREE-BASED MEMETIC ALGORITHM
In this paper, we consider the step fixed-charge transportation problem (FCTP) in which a step fixed cost, sometimes called a setup cost, is incurred if another related variable assumes a nonzero value. In order to solve the problem, two metaheuristic, a spanning tree-based genetic algorithm (GA) and a spanning tree-based memetic algorithm (MA), are developed for this NP-hard problem. For compa...
متن کامل