A comparison of different recombination operators for the 2-dimensional strip packing problem

In this paper, the three-stage two-dimensional rectangular strip packing problem is tackled using genetic algorithms. A new problem dependent recombination operator, called best inherited levels recombination (BIL), is introduced. A comparison of its performance is carried out with respect to four classical recombination operators. A complete study of the influence of the recombination operators on the genetic search, including the trade-off between exploration and exploitation in the search process, is presented. The results show that the use of our specialized BIL recombination outperforms the others more generic on all problem instances for all the metrics testedVII Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Cellular Genetic Algorithms: Understanding the Behavior of Using Neighborhoods

In this paper, we analyze the neighborhood effect in the selection of parents on an evolutionary algorithm. In this line, we compare a cellular genetic algorithm (cGA), which intrinsically uses the neighbor notion in the mating process, with a modified genetic algorithm including the concept of neighborhood in the selection of parents. Additionally, we analyze the neighborhood size considered for the selection of parent, trying to discover if a quasi-optimal size exists. All the analysis is carried out from a traditional analytic sense to a theoretical point of view regarding evolvability measures. The experimental results suggest that the neighbor effect is important in the performance of an evolutionary algorithm and could provide the cGA with higher chances of success in well-known optimization problems. Regarding the neighborhood size, there is an evidence that a range of neighbors of six, plus/minus two, individuals leads to the cGA to perform more efficiently than other considered sizes.Fil: Salto, Carolina. Universidad Nacional de La Pampa. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; ArgentinaFil: Alba, Enrique. Universidad de Málaga; Españ

Algoritmo de colonia de abejas artificiales hibridado con algoritmos evolutivos

In this paper, we design, implement, and analysis the replacement of the method to create new solutions in artificial bee colony algorithm by recombination operators, since the original method is similar to the recombination process used in evolutionary algorithms. For that purpose, we present a systematic investigation of the effect of using six different recombination operators for real-coded representations at the employed bee step. All the analysis is carried out using well known test problems. The experimental results suggest that the method to generate a new candidate food position plays an important role in the performance of the algorithm. Computational results and comparisons show that three of the six proposed algorithms are very competitive with the traditional bee colony algorithm.En este trabajo, se ha diseñado, implementado y analizado el reemplazo del método para crear nuevas soluciones en algoritmos basados en colonia de abejas artificiales por operadores de recombinación, ya que el método original es similar al proceso de recombinación usado en los algoritmos evolutivos. Para cumplir con este propósito, se presenta una investigación sistemática del efecto de usar seis operadores de recombinación distintos en el procedimiento llevado a cabo por la abeja empleada. Para la experimentación se utilizan casos de pruebas complejos, habitualmente utilizados en la literatura. Los resultados obtenidos sugieren que el método generador de nuevas fuentes de comida afecta el desempeño del algoritmo. A partir del análisis y comparaciones de los resultados, se observa que tres de las seis propuestas algorítmicas son competitivas con respecto al algoritmo basado en colonia de abejas tradicional.Facultad de Informátic

Algoritmo de colonia de abejas artificiales hibridado con algoritmos evolutivos

In this paper, we design, implement, and analysis the replacement of the method to create new solutions in artificial bee colony algorithm by recombination operators, since the original method is similar to the recombination process used in evolutionary algorithms. For that purpose, we present a systematic investigation of the effect of using six different recombination operators for real-coded representations at the employed bee step. All the analysis is carried out using well known test problems. The experimental results suggest that the method to generate a new candidate food position plays an important role in the performance of the algorithm. Computational results and comparisons show that three of the six proposed algorithms are very competitive with the traditional bee colony algorithm.En este trabajo, se ha diseñado, implementado y analizado el reemplazo del método para crear nuevas soluciones en algoritmos basados en colonia de abejas artificiales por operadores de recombinación, ya que el método original es similar al proceso de recombinación usado en los algoritmos evolutivos. Para cumplir con este propósito, se presenta una investigación sistemática del efecto de usar seis operadores de recombinación distintos en el procedimiento llevado a cabo por la abeja empleada. Para la experimentación se utilizan casos de pruebas complejos, habitualmente utilizados en la literatura. Los resultados obtenidos sugieren que el método generador de nuevas fuentes de comida afecta el desempeño del algoritmo. A partir del análisis y comparaciones de los resultados, se observa que tres de las seis propuestas algorítmicas son competitivas con respecto al algoritmo basado en colonia de abejas tradicional.Facultad de Informátic

Algoritmo de colonia de abejas artificiales hibridado con algoritmos evolutivos

In this paper, we design, implement, and analysis the replacement of the method to create new solutions in artificial bee colony algorithm by recombination operators, since the original method is similar to the recombination process used in evolutionary algorithms. For that purpose, we present a systematic investigation of the effect of using six different recombination operators for real-coded representations at the employed bee step. All the analysis is carried out using well known test problems. The experimental results suggest that the method to generate a new candidate food position plays an important role in the performance of the algorithm. Computational results and comparisons show that three of the six proposed algorithms are very competitive with the traditional bee colony algorithm.En este trabajo, se ha diseñado, implementado y analizado el reemplazo del método para crear nuevas soluciones en algoritmos basados en colonia de abejas artificiales por operadores de recombinación, ya que el método original es similar al proceso de recombinación usado en los algoritmos evolutivos. Para cumplir con este propósito, se presenta una investigación sistemática del efecto de usar seis operadores de recombinación distintos en el procedimiento llevado a cabo por la abeja empleada. Para la experimentación se utilizan casos de pruebas complejos, habitualmente utilizados en la literatura. Los resultados obtenidos sugieren que el método generador de nuevas fuentes de comida afecta el desempeño del algoritmo. A partir del análisis y comparaciones de los resultados, se observa que tres de las seis propuestas algorítmicas son competitivas con respecto al algoritmo basado en colonia de abejas tradicional.Facultad de Informátic

Improving Artificial Bee Colony Algorithm with Evolutionary Operators

In this paper, we analyze the effect of replacing the method to create new solutions in artificial bee colony algorithm by recombination operators. Since the original method is similar to the recombination process used in evolutionary algorithms. For that purpose, we present a systematic investigation of the effect of using six different recombination operators for real-coded representations at the employed bee step. All analysis is carried out using well known test problems. The experimental results suggest that the method to generate a new candidate food position plays an important role in the performance of the algorithm.Eje: XVIII Workshop de Agentes y Sistemas Inteligentes (WASI).Red de Universidades con Carreras en Informática (RedUNCI

A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem

This paper addresses the Flexible Job Shop Scheduling Problem (FJSSP) where the objective is to minimize the makespan. We develop a parallel hybrid Differential Evolution (DE) algorithm to tackle this problem. A random key representation of the FJSSP is adopted, which requires a very simple conversion mechanism to obtain a feasible schedule. This allows the DE algorithm to work on the continuous domain to explore the problem space of the discrete FJSSP. Moreover, a simple local search algorithm is embedded in the DE framework to balance the exploration and exploitation by enhancing the local searching ability. In addition, parallelism of the DE operations is included to improve the efficiency of whole algorithm. Experiments confirm the significant improvement achieved by integrating the propositions introduced in this study. Additional, test results show that our algorithm is competitive when compared with most existing approaches for the FJSSP.XX Workshop Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informátic

A comparison of different recombination operators for the 2-dimensional strip packing problem

In this paper, the three-stage two-dimensional rectangular strip packing problem is tackled using genetic algorithms. A new problem dependent recombination operator, called best inherited levels recombination (BIL), is introduced. A comparison of its performance is carried out with respect to four classical recombination operators. A complete study of the influence of the recombination operators on the genetic search, including the trade-off between exploration and exploitation in the search process, is presented. The results show that the use of our specialized BIL recombination outperforms the others more generic on all problem instances for all the metrics testedVII Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem

This paper addresses the Flexible Job Shop Scheduling Problem (FJSSP) where the objective is to minimize the makespan. We develop a parallel hybrid Differential Evolution (DE) algorithm to tackle this problem. A random key representation of the FJSSP is adopted, which requires a very simple conversion mechanism to obtain a feasible schedule. This allows the DE algorithm to work on the continuous domain to explore the problem space of the discrete FJSSP. Moreover, a simple local search algorithm is embedded in the DE framework to balance the exploration and exploitation by enhancing the local searching ability. In addition, parallelism of the DE operations is included to improve the efficiency of whole algorithm. Experiments confirm the significant improvement achieved by integrating the propositions introduced in this study. Additional, test results show that our algorithm is competitive when compared with most existing approaches for the FJSSP.XX Workshop Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informátic

A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem

This paper addresses the Flexible Job Shop Scheduling Problem (FJSSP) where the objective is to minimize the makespan. We develop a parallel hybrid Differential Evolution (DE) algorithm to tackle this problem. A random key representation of the FJSSP is adopted, which requires a very simple conversion mechanism to obtain a feasible schedule. This allows the DE algorithm to work on the continuous domain to explore the problem space of the discrete FJSSP. Moreover, a simple local search algorithm is embedded in the DE framework to balance the exploration and exploitation by enhancing the local searching ability. In addition, parallelism of the DE operations is included to improve the efficiency of whole algorithm. Experiments confirm the significant improvement achieved by integrating the propositions introduced in this study. Additional, test results show that our algorithm is competitive when compared with most existing approaches for the FJSSP.XX Workshop Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informátic