Advanced Intelligent Computing Theories and Applications. by Xuesong Yan, Qinghua Wu, Zhihua Cai (auth.), De-Shuang

By Xuesong Yan, Qinghua Wu, Zhihua Cai (auth.), De-Shuang Huang, Donald C. Wunsch II, Daniel S. Levine, Kang-Hyun Jo (eds.)

This booklet - along side the 2 volumes LNCS 5226 and LNAI 5227 - constitutes the refereed complaints of the Fourth foreign convention on clever Computing, ICIC 2008, held in Shanghai, China in September 2008.

The clever computing know-how incorporates a variety of ideas equivalent to man made intelligence, perceptual and development reputation, evolutionary and adaptive computing, informatics theories and functions, computational neuroscience and bioscience, smooth computing, case established and limited reasoning, brokers, networking and desktop supported co-operative operating, human computing device interface matters.

ICIC subject matter unifies the image of latest clever computing concepts as an vital idea that highlights the tendencies in complicated computational intelligence and bridges theoretical examine with applications.

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Extra info for Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques: 4th International Conference on Intelligent Computing, ICIC 2008 Shanghai, China, September 15-18, 2008 Proceedings

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1 Mathematical Formulation of Optimization Problem In this section formulation of optimal HV substation placement and feeders routing is presented in detail. The cost function for optimal distribution system planning is obtained from (1). J n =1 The fitness function that should be maximized is as (3) F= 1 CFFR The parameters used in equations (11) and (12) are defined as follow: CFFR : Cost function to be minimized TSN : Total substation number TFN : Total MV feeder number SC ( S i ) : The cost of HV substation S i SC ( Fi ) : The cost of HV substation S i I ( Fi ) : The Line current of feeder Fi Fi : Feeder i Ri : Resistance of feeder i n : Number of feeder sections L : Number of loops in the network K : Number of feeder sections in the network N : Number of MV substations connected to a feeder J : Number of HV substations I max : Maximum loading of feeder sections VDMV max : Acceptable voltage in downstream feeders V LL : Line voltage CAP : HV substation capacity (3) A New GA – Based and Graph Theory Supported Distribution System Planning 11 Table 1.

Jajodia, S. ) Proc. of the 1996 ACM SIGMOD Int’l Conf. on Management of Data, pp. 207–216. ACM Press, New York (1993) 6.

Qk: the max capacity of the kth vehicle. Dk: the max distance of the kth vehicle. nk: the number of customers dispatched by the kth vehicle. Rk: the set of customers dispatched by the kth vehicle. When nk=0, Rk=Φ. When nk≠0, { Rk = rk 1 , rki , } , rknk ⊆ {1, 2, dispatched sequence of the kth vehicle. S: the total cost of one solution. , M } , where rki is the ith customer in the 26 W. -Y. Zhou Fig. 1. An example of VRP The model is: F = min(S), where K ⎛ nk ⎞ S = ∑ ⎜ ∑ d rki−1rki + d rknk 0 ⎟ ⋅ sgn ( nk ) with k =1 ⎝ i =1 ⎠ constraint ⎧1, n ≥ 1 sgn ( nk ) = ⎨ k ⎩0, nk = 0 nk ∑q i =1 nk ∑d i =1 rki −1rki rki (4) ≤ Qk nk≠0 (5) + d rknk 0 ≤ Dk nk≠0 Rk1 ∩ Rk 2 = Φ k1≠k2 K ∪ Rk = {1, 2, k =1 (6) (7) K M } 0 ≤ nk ≤ M , ∑ nk = M (8) k =1 4 Ant Colony for VRP In ant colony model, an individual ant simulates a vehicle, and its route is constructed by incrementally selecting customers until all customers have been visited.

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