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The paper aims to develop a refrigerated-container loading problem (R-CLP) model for perishable fishery products in a cold chain. The novelty of this study is to enhance the models and algorithms of CLP to deal with two different temperatures in reefers: those of cargoes and those of containers. This research considers synchronising the required optimum temperature of products and the internal temperature distribution of reefers to minimise the quality deterioration of the products. The objective of the R-CLP is to minimise total loading costs while fulfiling quality requirement of the products. The quality requirement is based on the temperature distribution inside the reefer, which was obtained by computational fluid dynamics (CFD) simulation. The model includes traditional loading constraints of CLP. Moreover, this research has developed a heuristics algorithm that deals with various types of products, cargo box dimensions and temperature distribution data. A prototype application has been developed to simulate the loading plan visually using an application prototype named REFLOAD. The numerical experiment shows the ability of the model to minimise the quality loss while maintaining the utilisation of the reefer. The R-CLP algorithm can reduce the total loading costs to about 16% compared with those of CLP algorithm.

The development of the refrigerated-container loading problem model for perishable fishery products considering internal temperature distribution