Workforce Distribution Dynamic Multiagent by Millán Ruiz David (4 results)

Condition: New.

Taschenbuch. Condition: Neu. Neuware -This work describes a novel approach to the problem of workforce distribution in dynamic multi-agent systems based on blackboard architectures, focusing especially on a real-world scenario: the multi-skill call centre. Traditionally, to address such highly-dynamic environments, diverse greedy heuristics have been applied to provide solutions in real-time. Basically, these heuristics perform a continuous re-planning on the system, taking into account its current state at all times. As decisions are greedily taken, the distribution of the workforce may be poor in the medium and/or long term. The usage of parallel memetic algorithms, which are more sophisticated than standard ad-hoc heuristics, can lead us towards much more accurate solutions. In order to effectively apply parallel memetic algorithms to such a dynamic environment, we introduce the concept of adaptive time window. Thus, the size of the time window depends upon the level of dynamism of the system at a given time. This research proposes a set of tools to automatically determine the dynamism of the system, as well as a novel and precise prediction module based on a neural network and a powerful optimization method.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 252 pp. Englisch.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work describes a novel approach to the problem of workforce distribution in dynamic multi-agent systems based on blackboard architectures, focusing especially on a real-world scenario: the multi-skill call centre. Traditionally, to address such highly-dynamic environments, diverse greedy heuristics have been applied to provide solutions in real-time. Basically, these heuristics perform a continuous re-planning on the system, taking into account its current state at all times. As decisions are greedily taken, the distribution of the workforce may be poor in the medium and/or long term. The usage of parallel memetic algorithms, which are more sophisticated than standard ad-hoc heuristics, can lead us towards much more accurate solutions. In order to effectively apply parallel memetic algorithms to such a dynamic environment, we introduce the concept of adaptive time window. Thus, the size of the time window depends upon the level of dynamism of the system at a given time. This research proposes a set of tools to automatically determine the dynamism of the system, as well as a novel and precise prediction module based on a neural network and a powerful optimization method. 252 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work describes a novel approach to the problem of workforce distribution in dynamic multi-agent systems based on blackboard architectures, focusing especially on a real-world scenario: the multi-skill call centre. Traditionally, to address such highly-dynamic environments, diverse greedy heuristics have been applied to provide solutions in real-time. Basically, these heuristics perform a continuous re-planning on the system, taking into account its current state at all times. As decisions are greedily taken, the distribution of the workforce may be poor in the medium and/or long term. The usage of parallel memetic algorithms, which are more sophisticated than standard ad-hoc heuristics, can lead us towards much more accurate solutions. In order to effectively apply parallel memetic algorithms to such a dynamic environment, we introduce the concept of adaptive time window. Thus, the size of the time window depends upon the level of dynamism of the system at a given time. This research proposes a set of tools to automatically determine the dynamism of the system, as well as a novel and precise prediction module based on a neural network and a powerful optimization method.