Marriage in honeybee optimization to scheduling problems

Pedro Palominos, Victor Parada, Gustavo Gatica, Andrés Véjar

Resultado de la investigación: Contribución a los tipos de informe/libroCapítulo

Resumen

The biological inspired optimization techniques have proven to be powerful tools for solving scheduling problems. Marriage in Honeybee Optimization is a recent biological technique that attempts to emulate the social behavior in a bee colony and although has been applied to only a limited number of problems, it has delivered promising results. By means of this technique in this chapter the authors explore the solution space of scheduling problems by identifying an appropriate representation for each studied case. Two cases were considered: the minimization of earliness-tardiness penalties in a single machine scheduling and the permutation flow shop problem. The performance was evaluated for the first case with 280 instances from the literature. The technique performed quite well for a wide range of instances and achieved an average improvement of 1.4% for all instances. They obtained better solutions than the available upper bound for 141 instances. In the second case, they achieved an average error of 3.5% for the set of 120 test instances.

Idioma originalInglés
Título de la publicación alojadaHybrid Algorithms for Service, Computing and Manufacturing Systems
Subtítulo de la publicación alojadaRouting and Scheduling Solutions
EditorialIGI Global
Páginas158-177
Número de páginas20
ISBN (versión impresa)9781613500866
DOI
EstadoPublicada - 1 dic 2011

Áreas temáticas de ASJC Scopus

  • Empresa, gestión y contabilidad (todo)

Huella Profundice en los temas de investigación de 'Marriage in honeybee optimization to scheduling problems'. En conjunto forman una huella única.

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    Palominos, P., Parada, V., Gatica, G., & Véjar, A. (2011). Marriage in honeybee optimization to scheduling problems. En Hybrid Algorithms for Service, Computing and Manufacturing Systems: Routing and Scheduling Solutions (pp. 158-177). IGI Global. https://doi.org/10.4018/978-1-61350-086-6.ch008