Strategic design and multi-objective optimisation of distribution networks based on genetic algorithms

References

• Altiparmak , F. 2006 . A genetic algorithm approach for multi-objective optimization of supply chain networks . Computers & Industrial Engineering , 51 ( 1 ) : 196 – 215 .
   Web of Science ®Google Scholar
• Altiparmak , F. 2009 . A steady-state genetic algorithm for multi-product supply chain network design . Computers & Industrial Engineering , 56 ( 2 ) : 521 – 537 .
   Web of Science ®Google Scholar
• Ambrosino , D. and Scutellà , M.G. 2005 . Distribution network design: new problems and related models . European Journal of Operational Research , 165 : 610 – 624 .
   Web of Science ®Google Scholar
• Aytug , H. , Khouja , M. and Vergara , F.E. 2003 . Use of genetic algorithms to solve production and operations management: a review . International Journal of Production Research , 41 ( 17 ) : 3955 – 4009 .
   Web of Science ®Google Scholar
• Bevilacqua , V. A novel multi-objective genetic algorithm approach to artificial neural network topology optimisation: The breast cancer classification problem . 2006 International Joint Conference on Neural Networks . July 16–21 . Vancouver , , BC, Canada
   Google Scholar
• Burkey , M.L. 2011 . Spatial pricing models with lumpy transportation costs: the case for travel cost subsidization . Letters in Spatial and Resource Sciences , 4 ( 3 ) : 197 – 206 .
   Google Scholar
• Chan , F.T.S. 2006 . Design and performance evaluation of a distribution network – a simulation approach . International Journal of Advanced Manufacturing Technology , 29 : 814 – 825 .
   Web of Science ®Google Scholar
• Chan , F.T.S. and Chung , S.H. 2004 . A multi-criterion genetic algorithm for order distribution in a demand driven supply chain . International Journal of Computer Integrated Manufacturing , 17 ( 4 ) : 339 – 351 .
   Web of Science ®Google Scholar
• Chan , F.T.S. , Chung , S.H. and Wadhwa , S. 2004 . A hybrid genetic algorithm for production and distribution . Omega , 33 : 345 – 355 .
   Web of Science ®Google Scholar
• Chopra , S. 2003 . Designing the distribution network in a supply chain . Transportation Research Part E , 39 : 123 – 140 .
   Google Scholar
• Costantino , N. A model for the optimal design of the hospital drug distribution chain . Proceedings of the IEEE Workshop on Health Care Management . February 18–20 . Venice , , Italy
   Google Scholar
• Dimopoulos , C. and Zalzala , A.M.S. 2000 . Recent developments in evolutionary computation for manufacturing optimization: problems, solutions and comparisons . IEEE Transactions on Evolutionary Computation , 4 ( 2 ) : 93 – 113 .
   Web of Science ®Google Scholar
• Ding , H. , Benyoucef , L. and Xie , X. 2005 . A simulation optimization methodology for supplier selection problem . International Journal of Computer Integrated Manufacturing , 18 ( 2–3 ) : 210 – 224 .
   Web of Science ®Google Scholar
• Dotoli , M. and Falagario , M. 2011 . A hierarchical model for optimal supplier selection in multiple sourcing contexts . International Journal of Production Research , doi: 10.1080/00207543.2011.578167
   Web of Science ®Google Scholar
• Dotoli , M. , Fanti , M.P. and Mangini , A.M. 2007 . Fuzzy multi-objective optimization for network design of integrated e-supply chains . International Journal of Computer Integrated Manufacturing , 20 ( 6 ) : 588 – 601 .
   Web of Science ®Google Scholar
• Ehrgott , M. 2000 . Multicriteria optimization , Berlin-Heidelberg : Springer-Verlag .
   Google Scholar
• Holland , J.H. 1975 . Adaptation in natural and artificial systems , Ann Arbor : University of Michigan Press .
   Google Scholar
• Jang , Y.-J. 2002 . A combined model of network design and production/distribution planning for a supply network . Computers & Industrial Engineering , 43 : 263 – 281 .
   Web of Science ®Google Scholar
• Joines , J.A. Supply chain multi-objective simulation optimization . J.L. Snowdon and J.M. Charnes, eds. Proceedings of the 34th Winter simulation conference: exploring new frontiers, Vol. 2 . December 8–11 . pp. 1306 – 1314. ISBN 0-7803-7615-3 . San Diego : California. ACM .
   Google Scholar
• Melo , M.T. , Nickel , S. and Saldanha-da-Gama , F. 2009 . Facility location and supply chain management – a review . European Journal of Operational Research , 196 ( 2 ) : 401 – 412 .
   Web of Science ®Google Scholar
• Menolascina , F. 2008 . A multi-objective genetic algorithm based approach to the optimization of oligonucleotide microarray production process . Lecture Notes in Computer Science , vol. LNAI 5227, 1039–1046, ISSN: 0302-9743
   Google Scholar
• Michalewicz , Z. 1996 . GeneticAlgorithms + Data Structures = Evolution Programs , 3rd ed , AI Series. New York : Springer-Verlag .
   Google Scholar
• Miranda , P.A. , Garrido , R.A. and Ceroni , J.A. 2009 . E-Work based collaborative optimization approach for strategic logistic network design problem . Computers & Industrial Engineering , 57 : 3 – 13 .
   Web of Science ®Google Scholar
• Park , Y-B. and Hong , S-C. 2009 . Integrated production and distribution planning for single-period inventory products . International Journal of Computer Integrated Manufacturing , 22 ( 5 ) : 443 – 457 .
   Web of Science ®Google Scholar
• Pirard , F. , Iassinovski , S. and Riane , F. 2008 . A generic scalable simulation model for strategic supply chain management with emphasis on production activities . International Journal of Computer Integrated Manufacturing , 21 ( 4 ) : 455 – 467 .
   Web of Science ®Google Scholar
• Rath , K.P. and Zhao , G. 2001 . Two stage equilibrium and product choice with elastic demand . International Journal of Industrial Organization , 19 : 1441 – 1455 .
   Web of Science ®Google Scholar
• Samaranayake , P. , Laosirihongthong , T. and Chan , F.T.S. 2011 . Integration of manufacturing and distribution networks in a global car company – network models and numerical simulation . International Journal of Production Research , 49 ( 11 ) : 3127 – 3149 .
   Web of Science ®Google Scholar
• Shin , K.H. 2010 . Performance trajectory-based optimised supply chain dynamics . International Journal of Computer Integrated Manufacturing , 23 ( 1 ) : 87 – 100 .
   Web of Science ®Google Scholar
• Syarif , A. , Yun , Y.S. and Gen , M. 2002 . Study on multi-stage logistic chain network: a spanning tree-based genetic algorithm approach . Computers & Industrial Engineering , 43 ( 1–2 ) : 299 – 314 .
   Web of Science ®Google Scholar
• Yin , X.F. and Khoo , L.P. 2007 . Multiple population search strategy for routing selection and sequence optimization of a supply chain . International Journal of Computer Integrated Manufacturing , 20 ( 1 ) : 39 – 56 .
   Web of Science ®Google Scholar
• Zanjirani , Farahani, R. and Elahipanaha , M. 2008 . A genetic algorithm to optimize the total cost and service level for just-in-time distribution in a supply chain . International Journal of Production Economics , 111 : 229 – 243 .
   Web of Science ®Google Scholar