MCDM'19 - paper no. 8
ROBUST OPTIMISATION METAHEURISTICS FOR THE INVENTORY-ALLOCATION PROBLEM
Tea Vizinger, Janez Žerovnik
Abstract:
As an example of a successful application of a relatively simple metaheuristics for a stochastic version of a multiple criteria optimization problem, the inventory-allocation problem is discussed. Stochastic programming is introduced to deal with the demand of end consumers. It has been shown before that simple metaheuristics, i.e., local search may be a very competitive choice for solving computationally hard optimization problems. In this paper, robust optimization approach is applied to select more promising initial solutions which results in a significant improvement of time complexity of the optimization algorithms. Furthermore, it allows more flexibility in choosing the final solution that need not always be minimizing the sum of costs.
Keywords:
robust optimization, local search, stochastic programming, distribution
Reference index:
Tea Vizinger, Janez Žerovnik, (2019), ROBUST OPTIMISATION METAHEURISTICS FOR THE INVENTORY-ALLOCATION PROBLEM, Multiple Criteria Decision Making (14), pp. 129-143
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