Optimizing individual resource assignment using genetic algorithm

We present a hybrid algorithm based on Genetic Algorithms and Discrete Event Simulation that computes the algorithmic-optimal location of emergency resources. Parameters for the algorithm were obtained from computed historical statistics of the Bogotá Emergency Medical Services. Considerations taken into account are: (1) no more than a single resource is sent to an incident, (2) resources are selected according to incidentpriorities (3) distance from resource base to incident location is also considered for resource assignment and (4) all resources must be used equally. For every simulation, a different set of random incidents is generated so it’s possible to use the algorithm with an updated set of historical incidents. We found that the genetic algorithm converges so we can consider its solution as an optimal. With the algorithmic-optimal solution we found that arrival times are shorter than the historical ones. It’s also possible to compute the amount of required resources to reduce even more the arrival times. Since every Discrete Event Simulation takes a considerable amount of time the whole algorithm takes a heavy amount of time for large simulation time-periods and for many individuals for generation in the genetic algorithm, so an optimization approach is the next step in our research. Also, less restricted considerations must be taken into account for future developments in this topic.

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A Lamarckian Hybrid Grouping Genetic Algorithm with repair heuristics for resource assignment in WCDMA networks

Applied Soft Computing ◽

10.1016/j.asoc.2016.01.046 ◽

2016 ◽

Vol 43 ◽

pp. 619-632 ◽

Cited By ~ 5

Author(s):

L. Cuadra ◽

A. Aybar-Ruíz ◽

M.A. del Arco ◽

J. Navío-Marco ◽

J.A. Portilla-Figueras ◽

...

Keyword(s):

Genetic Algorithm ◽

Resource Assignment ◽

Grouping Genetic Algorithm

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Balancing Global Project Resources Utilising a Genetic Algorithm Approach with Stochastic Resource Assignments

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.10-12.67 ◽

2007 ◽

Vol 10-12 ◽

pp. 67-72

Author(s):

J. Lancaster ◽

Kai Cheng

Keyword(s):

Genetic Algorithm ◽

Resource Assignment ◽

Construction Companies ◽

Detail Design ◽

Design Detail ◽

Genetic Algorithm Approach ◽

Project Scheduling Problem ◽

Multiple Resource ◽

Algorithm Implementation ◽

A Company

Globalisation in large engineering, procurement and construction companies has lead in many cases to the establishment of a number of global centres for activities such as process design, detail design, procurement and fabrication. A company with a number of such resources then faces the problem of maintaining a high percentage utilisation in each of these resource locations, multiple projects need to be processed through each of these offices and which project is handled by which office is generally more reliant on available capacity than geography, particularly in the case of engineering centres. This paper considers this problem as an extension of the well studied Resource Constrained Project Scheduling Problem (RCPSP) and utilises a modified form of our existing genetic algorithm to optimise the utilisation of multiple resource locations when scheduling multiple projects. The unique aspect of this genetic algorithm implementation is its use of stochastic resource assignments to simulate the assignment of certain of the project activities to different global facilities. The stochastic resource assignment is processed as an extension to the main chromosome and is therefore optimised along with the scheduling sequence.

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