@article{(Open Science Index):https://publications.waset.org/pdf/15279,
	  title     = {Multi-matrix Real-coded Genetic Algorithm for Minimising Total Costs in Logistics Chain Network},
	  author    = {Pupong Pongcharoen and  Aphirak Khadwilard and  Anothai Klakankhai},
	  country	= {},
	  institution	= {},
	  abstract     = {The importance of supply chain and logistics
management has been widely recognised. Effective management of
the supply chain can reduce costs and lead times and improve
responsiveness to changing customer demands. This paper proposes a
multi-matrix real-coded Generic Algorithm (MRGA) based
optimisation tool that minimises total costs associated within supply
chain logistics. According to finite capacity constraints of all parties
within the chain, Genetic Algorithm (GA) often produces infeasible
chromosomes during initialisation and evolution processes. In the
proposed algorithm, chromosome initialisation procedure, crossover
and mutation operations that always guarantee feasible solutions
were embedded. The proposed algorithm was tested using three sizes
of benchmarking dataset of logistic chain network, which are typical
of those faced by most global manufacturing companies. A half
fractional factorial design was carried out to investigate the influence
of alternative crossover and mutation operators by varying GA
parameters. The analysis of experimental results suggested that the
quality of solutions obtained is sensitive to the ways in which the
genetic parameters and operators are set.},
	    journal   = {International Journal of Economics and Management Engineering},
	  volume    = {1},
	  number    = {11},
	  year      = {2007},
	  pages     = {574 - 579},
	  ee        = {https://publications.waset.org/pdf/15279},
	  url   	= {https://publications.waset.org/vol/11},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 11, 2007},