Combining a hybrid genetic algorithm and a heat transfer model to optimise an insulated box for use in the transport of perishables.
Temperature sensitive products are often transported in non-refrigerated systems, protected from environmental temperatures by thermal insulation and the provision of a source of cold inside the package. This work presents a method for optimising the design of thermally insulated boxes for lowest cost (while ensuring that product temperatures are maintained within set limits) by combining a heat transfer model with genetic algorithm optimisation. An example optimisation problem is presented in which a temperature sensitive product is transported across the US and must be maintained between -1 and 8 degrees C. Independent optimisation operations successfully identified solutions that were very similar, though not identical, thereby providing confidence in the approach to determine optimal solutions to complex problems. The system developed provides a rapid method to optimise the design of an insulated box for minimum cost while maintaining the product in the appropriate temperature range.
East
A R
AR
Food Science Australia, P.O. Box 52, North Ryde, NSW 2113, Australia. a.r.east@massey.ac.nz
Smale
N J
NJ
D000465:Algorithms; D003365:Costs and Cost Analysis; D004349:Drug Packaging / Q000191:economics / Q000706:statistics & numerical data*; D004356:Drug Storage; D005823:Genetics / Q000706:statistics & numerical data*; D006358:Hot Temperature; D015233:Models, Statistical; D015203:Reproducibility of Results; D012984:Software; D013816:Thermodynamics; D014186:Transportation / Q000191:economics / Q000706:statistics & numerical data*