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Towards a software tool for general meal optimisation

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Abstract

The following work presents a software solution capable of designing general meal plans which approach an optimal match of nutritional characteristics submitted by the user. A thorough review of existing literature indicates the absence of a software solution to this problem in its most general form. Existing solutions tend to address particular forms of the problem in specific contexts, for example, optimising culturally typical diets in response to specific medical conditions. Conversely, this work focuses on developing a nutritional software model with sufficient flexibility to be described as general, paired with a simple, specifically designed optimisation algorithm for working with the proposed prototype system. The resulting software tool can express the following characteristics: arbitrary nutritional content; economic characteristics; binary food-type classifications (e.g. vegetarian); and, because of the optimisation framework, can capture goals for any number of meals; meal composition (combinations of recipes for a given meal at a particular time); a maximum economic cost per meal; and nutritional content within each meal. The work outlines a prototype user interface to enable nutritional data and user goals to be entered and validated. Finally, based on ten specific test problems containing varied dietary goals, a basic algorithm tuning approach is described. The results suggest that the proposed prototype system can address the general meal optimisation problem. There is a discussion of several future developments to improve system capabilities and usability further.

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Notes

  1. Cultural specificity refers to assumptions about the type of foods typically consumed, the format and timing of meals.

  2. The one displaying a lower fitness value in a maximisation context.

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Funding

No funding was received for conducting this study.

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Authors and Affiliations

  1. Institute of Artificial Intelligence, School of Computer Science and Informatics, De Montfort University, The Gateway, Leicester, UK

    James Izzard, Fabio Caraffini & Francisco Chiclana

  2. Andalusian Research Institute on Data Science and Computational Intelligence, University of Granada, Granada, Spain

    Francisco Chiclana

Authors
  1. James Izzard
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  2. Fabio Caraffini
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  3. Francisco Chiclana
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Correspondence to Fabio Caraffini.

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Supplementary information

The source code and all configurations files for testing the software are available via the institutional Figshare repository at [26]. Note that this is currently a private repository shared via the provided link. If the journal accepts the paper for publication, the DOI will be activated to make the paper public.

Availability of data and materials

Source code includes complete database used for testing.

Code availability

Our code is provided via an archive and a GitHub link through the institutional Figshare repository at [26].

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Izzard, J., Caraffini, F. & Chiclana, F. Towards a software tool for general meal optimisation. Appl Intell 53, 7751–7775 (2023). https://doi.org/10.1007/s10489-022-03935-0

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