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2013 | nr 1 (27) | 167--184
Tytuł artykułu

Use of genetic algorithms in supply chain management : literature review and current trends

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
For the past few decades SCM has been one of the main objectives in research and practice. Since that time researchers have developed a lot of methods and procedures which optimized this process. To create an efficient supply chain network the resources and factories must be tightly integrated. The most supply chain network designs have multiple layers, members, periods, products, and comparative resources constraints exist between different layers. Supply chain networks design is related to the problems which are very popular in literature. The subject of this paper is to present the variants, configurations and parameters of genetic algorithm (GA) for solving supply chain network design problems. We focus on references from 2000 to 2011. Furthermore, current trends are introduced and discussed. (original abstract)
Rocznik
Numer
Strony
167--184
Opis fizyczny
Twórcy
  • Szkoła Główna Handlowa w Warszawie
Bibliografia
  • Altiparmak F., Gen M., Lin L., Karaoglan I., A steady-state genetic algorithm for multi-product supply chain network design, "Computers & Industrial Engineering" 2009, No. 56.
  • Altiparmak F., Gen M., Lin L., Paksoy T., A genetic algorithm approach for multi-objective optimization of supply chain networks, "Computers & Industrial Engineering" 2006, No. 51.
  • Aytug H., Khouja M., Vergara F. E., Use of genetic algorithm to solve production and operations management problems: a review, "International Journal in Production Research" 2003, No. 41.
  • Chan F. T. S., Chung S. H., Multi-criteria genetic optimization for distribution network problems, "The International Journal of Advanced Manufacturing Technology" 2004, No. 24.
  • Chung S. H., Lau H. C. W., Choy K. L., Ho G. T. S., Tse Y. K., Application of genetic approach for advanced planning in multi-factory environment, "International Journal of Production Economics" 2010, No. 127.
  • Farahan R. Z., Elahipanah M., 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" 2008, No. 111.
  • Gen M., Altiparmak F., Lin L., A genetic algorithm for two-stage transportation problem using priority-based encoding, "OR Spectrum" 2006, No. 28.
  • Goldberg D. E., Algorytmy genetyczne i ich zastosowania, Wydawnictwo Naukowo-Techniczne, Warszawa 2003.
  • Herroelen W., Project scheduling - Theory and practice, "Production and Operations Management" 2005, No. 14.
  • Józefowska J., Zimniak A., A multiple criteria genetic algorithm operating on a reduce search space, in: Eds. S. Domek, R. Kaszyński, Proceedings of the 10th IEEE Conference on Methods and Models in Automation and Robotics. Międzyzdroje 2004.
  • Jung J. W., Lee Y. H., Heuristic algorithms for production and transportation planning through synchronization of a serial supply chain, "International Journal of Production Economics" 2010, No. 124.
  • Lim S. J., Jeong S. J., Kim K. S., Park M. W., Hybrid approach to distribution planning reflecting a stochastic supply chain, "The International Journal of Advanced Manufacturing Technology" 2006, No. 28.
  • Moon C., Kim J., Gen M., Advanced planning and scheduling based on precedence and resource constraints for e-plant chains, "International Journal of Production Research" 2004, No. 42.
  • Moon C., Seo Y., Yun Y., Gen M., Adaptive genetic algorithm for advanced planning in manufacturing supply chain, "Journal of Intelligent Manufacturing" 2006, No. 17.
  • Naso D., Surico M., Turchiano B., Kaymak U., Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete, "European Journal Of Operational Research" 2007, No. 177.
  • Papageorgiou L. G., Supply chain optimisation for the process industries: Advances and opportunities, "Computers and Chemical Engineering" 2009, No. 33.
  • Radhakrishnan P., Jeyanthi N., Genetic Algorithm Model for Multi-factory Supply Chain Inventory Optimization involving Lead Time, "International Journal of Computational Engineering & Management" 2011, No. 14.
  • Rostamian Delavar M., Hajiaghaei-Keshteli M., Molla-Alizadeh-Zavardehi S., Genetic algorithms for coordinated scheduling of production and air transportation, "Expert Systems with Applications" 2010, No. 37.
  • Syarif A., Yun Y. S., Gen M., Study on multi-stage logistic chain network: a spanning tree-based genetic algorithm approach, "Computers and Industrial Engineering" 2002, No. 43.
  • Węglarz J., Józefowska J., Mika M., Waligóra G., Project scheduling with finite or infinite number of activity processing modes - A survey, "European Journal of Operational Research" 2011, No. 208.
  • Yao M., Hsu H., A new spanning tree-based genetic algorithm for the design of multi-stage supply chain networks with nonlinear transportation costs, "Optimization and Engineering" 2009, No. 10.
  • Yimer A. D., Demirli K., A genetic approach to two-phase optimization of dynamic supply chain scheduling, "Computers & Industrial Engineering" 2010, No. 58.
  • Ying-Hua C., Adopting co-evolution and constraint-satisfaction concept on genetic algorithms to solve supply chain network design problems, "Expert Systems with Applications" 2010, No. 37.
  • Zegordi S. H., Abadi I. N. K., Nia M. A. B., A novel genetic algorithm for solving production and transportation scheduling in a two-stage supply chain, "Computers & Industrial Engineering" 2010, No. 58.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171273973

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