Multi-objective simulation optimization: A case study in healthcare management

    Authors

    F. F. Baesler;J. A. Sepulveda

    Comments

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    Abbreviated Journal Title

    Int. J. Ind. Eng.-Theory Appl. Pract.

    Keywords

    simulation; optimization; multi-objective; genetic algorithms; healthcare; GOAL PROGRAMMING APPROACH; MANUFACTURING SYSTEMS; MULTICRITERIA DESIGN; MODELS; Engineering, Industrial; Engineering, Manufacturing

    Abstract

    This study presents an approach to solve multi-response simulation optimization problems. This approach integrates a simulation model with a genetic algorithm heuristic and a goal programming model. This method was modified to perform the search considering the mean and the variance of the responses. This way, the selection process of the genetic algorithm is performed stochastically, and not deterministically like most of the approaches reported in the literature. The methodology was tested using a simulation model of a cancer treatment facility created by the authors. The multi-objective optimization heuristic was successfully used to improve the performance of the model relative to four different system objectives. Empirical results show that the methodology is capable of generating an important part of the Pareto optimal frontier, mostly concentrated in the center portion, where practical solutions are generally located.

    Journal Title

    International Journal of Industrial Engineering-Theory Applications and Practice

    Volume

    13

    Issue/Number

    2

    Publication Date

    1-1-2006

    Document Type

    Article

    Language

    English

    First Page

    156

    Last Page

    165

    WOS Identifier

    WOS:000246634900005

    ISSN

    1072-4761

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