Solving timetabling problems using a cultural algorithm

Soza, Carlos; Becerra, Ricardo Landa; Riff, María Cristina; Coello, Carlos A. Coello

doi:10.1016/j.asoc.2009.11.024

Cited by 43 publications

(18 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…From those theories, the cultural evolution can be thought of as an inheritance process according to the genetic material that an offspring inherits from its parents, and the knowledge acquired by individuals through generations that guides behavior of the individuals. The concept of CA has already found applications in a variety of areas, such as timetabling problem (Soza et al, 2011), economic load dispatch problem (dos Santos Coelho et al, 2009), multi-machine power system stabilizer (Khodabakhshian and Hemmati, 2013), extracting urban occupational plans (Jayyousi and Reynolds, 2014), among others.…”

Section: Cultural Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Spatial forest resource planning using a cultural algorithm with problem-specific information

Liu

Lin

2015

Environmental Modelling & Software

View full text Add to dashboard Cite

Section: Cultural Algorithmmentioning

confidence: 99%

“…In (Soza et al, 2011;Zhou et al, 2011), a parameter control mechanism for selecting the above three exploration operators was proposed as follows. The mechanism is based upon a roulette wheel and the successful rate of each operator.…”

Section: Exploration Operatorsmentioning

confidence: 99%

Spatial forest resource planning using a cultural algorithm with problem-specific information

Liu

Lin

2015

Environmental Modelling & Software

View full text Add to dashboard Cite

“…If any constraint is violated, the interchange is not executed. By analogy from [12], a parameter control mechanism is applied for selecting the above three exploration operators.…”

Section: Exploration Operatorsmentioning

confidence: 99%

A cultural algorithm for spatial forest harvest scheduling

Liu

Lin

2014

2014 IEEE Congress on Evolutionary Computation (CEC)

View full text Add to dashboard Cite

This paper proposes a cultural algorithm for the spatial forest harvest scheduling for maximizing the total harvested timber volume, under the constraints of minimum harvest age, minimum adjacency green-up age, and approximately even volume flow for each period of the schedule. In order to increase the solution-search ability, the cultural algorithm extracts problem-specific information during the evolutionary solution search to update the belief space of a generation, which has cultural influences and guidance on the next generation. The key design of our cultural algorithm is to propose the cultural and evolutionary operators specifically for the problem. Experimental analysis shows that our cultural algorithm performs better than the previous approaches.

show abstract

“…However, at the investigative level this proposal is not beyond the scope of previous work in which a wide variety of techniques have been applied to solve scheduling problem [2] based on models such as integer programming [3], [4] linear programming [5], Backtraking [6], [7] multi objectives scheduling [8] evolutionary algorithms [9], [10], [11] metaheuristics [12], mathematical models based on polynomial reduction [13], taboo search [14] and expert systems [15] among others [16], [17], [18].…”

Section: Introductionmentioning

confidence: 99%

Class Schedule Assignment Based on Students Learning Rhythms Using A Genetic Algorithm

2013

View full text Add to dashboard Cite

The objective of this proposal is to implement a school day agenda focused on the learning rhythms of students of elementary and secondary schools using a genetic algorithm. The methodology of this proposal takes into account legal requirements and constraints on the assignment of teachers and classrooms in public educational institutions in Colombia. In addition, this proposal provides a set of constraints focused on cognitive rhythms and subjects are scheduled at the most convenient times according to the area of knowledge. The genetic algorithm evolves through a process of mutation and selection and builds a total solution based on the best solutions for each group. Sixteen groups in a school are tested and the results of class schedule assignments 77|Class Schedule Assignment Based on Students Learning Rhythms Using A Genetic Algorithm are presented. The quality of the solution obtained through the established approach is validated by comparing the results to the solutions obtained using another algorithm. Key words:learning rhythms, genetic algorithm, class schedule, optimization, logistic. Highlights• The computational model presented is a genetic algorithm.• The methodology developed achieves an improvement of 12% (based on the rhythms as cognitive) than traditional algorithms generate schedules.• The algorithm shows high stability in the found solutions, ensuring an effieciency over 92% in the result obtained in each cycles. Asignación de horarios de clase basado en los ritmos de aprendizaje de los estudiantes usando un algoritmo genético ResumenEl objetivo de esta propuesta es implementar un horario escolar que tenga en cuenta los ritmos de aprendizaje en los estudiantes de educación primaria y secundaria, utilizando un algoritmo genético. La metodología considera los requerimientos legales y las restricciones necesarias para la asignación de maestros y aulas en instituciones educativas públicas de Colombia. Adicionalmente, se establecen un conjunto de restricciones relacionadas con el enfoque en los ritmos cognitivos, determinando las horas de la jornada en las que es más conveniente la ubicación de ciertas materias de acuerdo al área del conocimiento al que pertenecen. El algoritmo genético evoluciona mediante un proceso de mutación y selección, a través del cual se construye una solución completa a partir de la búsqueda de las mejores soluciones por grupo. Se presentan los resultados de las pruebas realizadas para la asignación de una institución con 16 grupos. La calidad de las soluciones obtenidas de acuerdo al enfoque establecido es validada mediante la comparación de los resultados obtenidos con las soluciones de otro algoritmo.Palabras clave: ritmos de aprendizaje, algoritmos genéticos, horario de clase, optimización, logística.

show abstract

Solving timetabling problems using a cultural algorithm

Cited by 43 publications

References 2 publications

Spatial forest resource planning using a cultural algorithm with problem-specific information

Spatial forest resource planning using a cultural algorithm with problem-specific information

A cultural algorithm for spatial forest harvest scheduling

Class Schedule Assignment Based on Students Learning Rhythms Using A Genetic Algorithm

Contact Info

Product

Resources

About