DEVELOPING MENU PLANNING SOFTWARE USING OPTIMIZATION AND ARTIFICIAL INTELLIGENCE ALGORITHM

Year 2024, Volume: 49 Issue: 5, 833 - 846, 10.10.2024

Fatih Tarlak

https://doi.org/10.15237/10.15237/gida.GD24063

Abstract

In today's world, awareness of health and nutrition is growing, emphasizing the need for personalized nutrition recommendations and reducing food waste. This study collected demographic data and food preferences from users and analyzed them using artificial intelligence models. A model developed with the Random Forest algorithm was trained to predict users' future preferences and guide menu planning. Tests showed that combining AI with optimization techniques successfully creates user-focused menus, enhancing satisfaction and reducing food waste. The study also highlighted challenges related to the dataset's size, pointing to a need for more qualitative data. The developed model provides innovative solutions for catering companies and institutions offering mass dining, improving employee satisfaction while minimizing waste. Future research aims to refine the model for broader applications.

Keywords

Artificial Intelligence, Optimization Algorithms, Linear Programming, Personalized Menu, Catering

OPTİMİZASYON VE YAPAY ZEKÂ ALGORİTMALARI KULLANARAK MENÜ PLANLAMA YAZILIMI GELİŞTİRİLMESİ

Abstract

Günümüzde sağlık ve beslenme bilinci giderek artmakta, bu da kişiye özel beslenme önerilerinin ve gıda israfının azaltılmasının önemini vurgulamaktadır. Bu çalışmada, kullanıcılardan demografik veriler ve gıda tercihleri toplanarak yapay zeka modelleri ile analiz edilmiştir. Random Forest algoritması kullanılarak geliştirilen bir model, kullanıcıların gelecekteki tercihlerini tahmin etmek ve menü planlamasına rehberlik etmek üzere eğitilmiştir. Yapılan testler, yapay zeka ve optimizasyon tekniklerinin birleştirilmesinin kullanıcı odaklı menüler oluşturduğunu, memnuniyeti artırdığını ve gıda israfını azalttığını göstermiştir. Çalışma ayrıca, veri setinin boyutuyla ilgili zorluklara dikkat çekerek, daha nitelikli verilere olan ihtiyacı ortaya koymuştur. Geliştirilen model, toplu yemek hizmeti sunan catering şirketleri ve diğer kurumlar için yenilikçi çözümler sunarak çalışan memnuniyetini artırırken israfı da minimize etmektedir. Gelecek araştırmalar, modelin daha geniş uygulamalar için geliştirilmesini hedeflemektedir.

Keywords

Artificial Intelligence, Optimization Algorithms, Linear Programming, Personalized Menu, Catering

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