Multi-Objective Genetic Local Search Algorithm for Supply Chain Simulation Optimisation

The International Conference on Harbor, Maritime & Multimodal Logistics Modelling and Simulation (HMS 2009) 2009
Gaļina Merkurjeva, Liāna Napalkova

This paper presents a hybrid simulation optimisation algorithm that integrates a multi-objective genetic algorithm and response surface-based metamodelling techniques. The optimisation problem involves a search in a high dimensional space with different ranges for decision variable scales, multiple stochastic objective functions and problem specific constraints. A case study demonstrates the application of a hybrid simulation optimisation algorithm to optimal cyclic planning for a generic supply chain network.

Keywords
simulation optimisation, genetic algorithm, response surface-based metamodelling, linear search, supply chain cyclic planning

Merkurjeva, G., Napalkova, L. Multi-Objective Genetic Local Search Algorithm for Supply Chain Simulation Optimisation. In: The International Conference on Harbor, Maritime & Multimodal Logistics Modelling and Simulation (HMS 2009), Spain, Puerto de la Cruz, Tenerife, 23-25 September, 2009. La Laguna: Universidad de La Laguna, 2009, pp.190-194. ISBN 978-84-692-5416-5.

Publication language
English (en)