By Hiroyuki Yoshida, Ashlesha Jain, Ajita Ichalkaranje, Nikhil Ichalkaranje
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Extra resources for Advanced Computational Intelligence Paradigms in Healthcare-2
000 runs. e. the best ﬁtness value of all solutions the allele was part of) with the weighted best ﬁtness values of its 8 neighbors. 2j) · (f [i − j] + f [i + j])] g[i] = f [i] + j=1 where f [i] is the ﬁtness of the ith allele. The trend curve (lower part) shows that solutions containing frequent alleles have generally better goodness. 3 Application of Artiﬁcial Intelligence for Weekly Dietary Menu Planning 43 The results show, that alleles appearing in good solutions are used more often by the algorithm and the frequency of usage is about inverse proportional to the ﬁtness of the best solution generated by using the particular allele.
The function is not necessarily symmetric to the optimum, because the eﬀects of the deviations from the optimal value can be diﬀerent in the negative and positive case. This sort of penalizing has been derived from the manual assessment methods of human nutrition experts. Fig. 1. The Fitness function with optimum = 300, lower limit = 100, upper limit = 700 34 B. Ga´ al et al. Fitness functions of this style are also often applied in other multi-objective optimization techniques . 5 Multi-level Organization There are several common features in the diﬀerent nutritional levels (meal plan, daily plan, weekly plan) of the problem space.
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