Menu planning using multi-complex differential evolution algorithm for wasting children

Abstract

Despite Indonesia's stable economic growth, child wasting remains high, particularly in Nusa Tenggara Timur (NTT) Province, reflecting a disparity between economic progress and public health. The complexity of this issue is exacerbated by the low level of women's education in NTT, while climatic factors and soil conditions further impact food availability. We used the Multi-Complex Differential Evolution algorithm to serve as an effective and efficient tool for mothers in planning a diverse selection of nutritious meals for their children based on food availability and parental economic capacity. The algorithm analyses local food resources and suggests meal plans that maximise nutritional value within available ingredients. Optimising food combinations ensures children receive balanced nutrition, addressing deficiencies contributing to child wasting. The findings indicate that this algorithm performs well with a population size of 30 and a maximum of 1,000 iterations using the DE/rand/1 mutation function. Moreover, with these parameters, the algorithm generates various healthy meal plans that meet multiple constraints while ensuring a short execution time.