Supply chain cyclic planning and optimisation

Simulation-Based Case Studies in Logistics: Education and Applied Research

Volumn , Issue , 2009, Pages 85-107

  Merkuryeva, Galina ^a   Napalkova, Liana ^a  

^a RIGA TECHNICAL UNIVERSITY   (Latvia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84892341717     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-1-84882-187-3_6     Document Type: Chapter

References (13)

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2. Campbell GM, Mabert VA (1991) Cyclical schedules for capacitated lot sizing with dynamic demands. Manag Sci 37:409-427
3. Merkuryeva G, Napalkova L (2007) Development of simulation-based environment for multi-echelon cyclic planning and optimisation. In: Proceedings 6th EUROSIM congress on modelling and simulation
4. Abraham A, Jain L, Goldberg R (2005) Evolutionary multiobjective optimisation: theoretical advances and applications. Springer, New York
5. Azadivar F (1992) A tutorial on simulation optimization. In: Proceedings 1992 winter simulation conference, pp 198-204
6. Merkuryev Y, Visipkov V (1994) A survey of optimization methods in discrete systems simulation. In: Proceedings frst joint conference of International Simulation Society, pp 104-110
7. Carson M, Maria A (1997) Simulation optimisation: methods and a pplications. In: Proceedings 1997 winter simulation conference, pp 118-126
8. Fu MC, Glover FW, April J (2005) Simulation optimisation: a review, new developments and a pplications. In: Proceedings 2005 winter simulation conference, pp 83-95
9. Konak A, Coit DW, Smoth AE (2006) Multi-objective optimisation using genetic algorithms: A tutorial. Reliab Eng Syst Saf 91:992-1007
10. Deb K, Pratap A, Agrawal S et al (2002) A fast elitist non-dominated sorting genetic algorithm for multi-objective optimisation: NSGA-II. IEEE Trans Evol Computat 6:182-197
11. Goldberg DE (1985) Optimal initial population size for binary-coded genetic algorithms. In: Technical Report TCGA-850001, University of Alabama, USA
12. Merkuryeva G (2005) Response surface-based simulation meta-modelling methods with applications to optimisation problems. In: Dolgui A et al (eds) Supply chain optimisation product/process design, facility location and fow control. Springer, New York
13. Chopra S, Meindl P (2001) Supply chain management: strategy, planning and operation. Pearson Education, Upper Saddle River, NJ