Packaging material selection (PMS) problems have always been important to packaging designers and engineers. Not only does the selection of packaging material determine the costs and the environmental impacts of packaging, but also influences packaging physical characteristics and associated manufacturing methods. In order to reduce economic and environmental impacts, one has to take a holistic approach to packaging material selection by considering material effects throughout the packaging life cycle. To evaluate economic costs and environmental impacts both quantitative factors and subjective criteria play an important role in the packaging design. In the present work, fuzzy set theory is used for representing and manipulating the vague and subjective descriptions of packaging performance and design attributes. Further a genetic algorithm based approach is used for addressing the packaging material selection problem through multiple criteria decision-making. The overall approach comprises of two phases. In the first phase, fuzzy set theory is used for the linguistic transformation of performance attributes into numerical values. It results in a decision matrix that contains crisp scores. Also in this phase, a weight is assigned to each sub-criterion to show its importance compared to others. In the second phase, a GA is used to globally search for near-optimal or optimal design solutions. The implementation of the proposed methodology is illustrated through a numerical example.


Originally published in the Proceedings of the SPIE International Conference on Environmentally Conscious Manufacturing IV


Packaging, Material selection, Multiple criteria decision-making, Genetic algorithms, Fuzzy set theory

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Production engineering, Recycling (Waste (etc.))





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