Highlights We propose a model for the organ transplant transportation network design. We present a fuzzy multi-objective programming approach to solve the problem. We present two meta-heuristics approaches to solve large problems. We provide a real industrial case-study and analyze the results.

    Abstract We propose a novel multi-period location–allocation model for the design of an organ transplant transportation network under uncertainty. The model consists of a bi-objective mathematical programming model that minimizes total cost and time, including waiting time in the queue for the transplant operation, while considering organs’ priorities. A fuzzy multi-objective programming based approach is presented to solve the small and medium size problems to optimality. For larger problems, we propose two meta-heuristics based algorithms. Lower bounds, and several numerical examples with managerial insights are discussed. A real case-study is provided, and the existing and the proposed optimal solutions are compared.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multi-objective design of an organ transplant network under uncertainty


    Contributors:


    Publication date :

    2014-09-20


    Size :

    24 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    Bayesian Network Approach to Multidisciplinary, Multi-Objective Design Optimization under Uncertainty

    Nannapaneni, Saideep / Liang, Chen / Mahadevan, Sankaran | AIAA | 2017


    Multi-Objective Optimization Under Uncertainty

    Liang, Chen / Mahadevan, Sankaran | AIAA | 2015



    BAYESIAN NETWORK APPROACH TO MULTIDISCIPLINARY, MULTI-OBJECTIVE DESIGN OPTIMIZATION UNDER UNCERTAINTY (AIAA 2017-3825)

    Nannapaneni, Saideep / Liang, Chen / Mahadevan, Sankaran | British Library Conference Proceedings | 2017