Generalized higher-level automated innovization with application to inventory management

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Bandaru:2015:EJOR,
  author =       "Sunith Bandaru and Tehseen Aslam and Amos H. C. Ng and 
                 Kalyanmoy Deb",
  title =        "Generalized higher-level automated innovization with
                 application to inventory management",
  journal =      "European Journal of Operational Research",
  volume =       "243",
  number =       "2",
  pages =        "480--496",
  year =         "2015",
  ISSN =         "0377-2217",
  DOI =          "doi:10.1016/j.ejor.2014.11.015",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0377221714009199",
  abstract =     "This paper generalises the automated innovization
                 framework using genetic programming in the context of
                 higher-level innovisation. Automated innovization is an
                 unsupervised machine learning technique that can
                 automatically extract significant mathematical
                 relationships from Pareto-optimal solution sets. These
                 resulting relationships describe the conditions for
                 Pareto-optimality for the multi-objective problem under
                 consideration and can be used by scientists and
                 practitioners as thumb rules to understand the problem
                 better and to innovate new problem solving techniques;
                 hence the name innovization (innovation through
                 optimisation). Higher-level innovization involves
                 performing automated innovization on multiple
                 Pareto-optimal solution sets obtained by varying one or
                 more problem parameters. The automated innovization
                 framework was recently updated using genetic
                 programming. We extend this generalisation to perform
                 higher-level automated innovization and demonstrate the
                 methodology on a standard two-bar bi-objective truss
                 design problem. The procedure is then applied to a
                 classic case of inventory management with
                 multi-objective optimisation performed at both system
                 and process levels. The applicability of automated
                 innovization to this area should motivate its use in
                 other avenues of operational research.",
  keywords =     "genetic algorithms, genetic programming, Automated
                 innovization, Higher-level innovization, Inventory
                 management, Knowledge discovery",
}

Genetic Programming entries for Sunith Bandaru Tehseen Aslam Amos H C Ng Kalyanmoy Deb

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