Agents endowed with uncertainty management behaviors to solve a multiskill healthcare task scheduling

Agents endowed with uncertainty management behaviors to solve a multiskill healthcare task scheduling

Health organizations are complex to manage due to their dynamic processes and distributed hospital organization. It is therefore necessary for healthcare institutions to focus on this issue to deal with patients' requirements. We aim in this paper to develop and implement a management decision support system (DSS) that can help physicians to better manage their organization and anticipate the f...

Scheduling Projects with Multiskill Learning Effect

We investigate the project scheduling problem with multiskill learning effect. A new model is proposed to deal with the problem, where both autonomous and induced learning are considered. In order to obtain the optimal solution, a genetic algorithm with specific encoding and decoding schemes is introduced. A numerical example is used to illustrate the proposed model. The computational results s...

Task Scheduling using Constraint Optimization with Uncertainty

Multiagent task scheduling encompasses diverse domains of problems that require complex models and robust solutions. C-TÆMS [1] is a new specification, based on TÆMS [2], for multiagent task scheduling problems that represents the complex relationships necessary to model these domains. Some recent work has been done in the area of mapping the C-TÆMS scheduling problem into a Distributed Constra...

Scheduling Multi-task Agents

Using ant colonies to solve multiprocessor task graph scheduling

The problem of scheduling a parallel program presented by a weighted directed acyclic graph (DAG) to the set of homogeneous processors for minimizing the completion time of the program has been extensively studied as academic optimization problem which occurs in optimizing the execution time of parallel algorithm with parallel computer. In this paper, we propose an application of the Ant Colony...