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By Hiroyuki Yoshida, Ashlesha Jain, Ajita Ichalkaranje, Nikhil Ichalkaranje

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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 [19]. 5 Multi-level Organization There are several common features in the different nutritional levels (meal plan, daily plan, weekly plan) of the problem space.

Journal of Happiness Studies 4 (2003) 35–52 52. : Comparing outcomes of major models for police responses to mental health emergencies. Psychiatric Services 51 (2000) 645–649 53. : Speech interaction and human behavior representations (HBRs). Computer Generated Forces and Behavioral Representation 10 (2001) 467–476 54. : Homeland security and virtual reality: building a strategic adaptive response system (STARS). Studies in Health Technology and Informatics 111 (2005) 549–555 55. Tak´ acs, B. (2005), Special education & rehabilitation: teaching and healing with interactive graphics.

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