2006 7 7 :100026788 (2006) 0720047207 1,3, 2 3, (11, 110004 21, 100084 31, 110016) :,,,,, : : TP18 C934 : A esearch on Hybrid Particle Swarm Optimization for Automobile Logistics Network Design Problem QIN Xu2wei 1,3, FAN Yu2shun 2, YIN Chao2wan 3 (11School of Business Administration, Northeastern University, Shenyang 110004, China 21Department of Automation, Tsinghua University, Beijing 100084, China 31Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China) Abstract: According to the practical operation characteristic of automobile logistics network, the integrated optimization model is presented, which provides an integrated view of transportation economies - of - scale, inventory and facility costs as well as service quality The solution combined the flow prediction algorithm and particle swarm optimization ( PSO) is presented In this solution, PSO is used to search feasible structure of logistics network, while flow prediction algorithm is used to decide its optimal transportation route Evolution operation such as crossover and mutation is also embedded to avoid the common defect of premature convergence Simulations are given to confirm this hybrid particle swarm optimization work efficiency and the probability of finding the global optimal value are enhanced Key words : automobile logistics flow prediction algorithm hybrid particle swarm optimization 0,, Nozick, (S - 1,S), [1 2 ], [2 ] Hall, [3 ] [4 ] 2, 2 (PSO),Kennedy Eberhart, :2005203224 : (70431003) : (1976 - ),,,, (1962 - ),,,,, 1994-2006 China Academic Journal Electronic Publishing House All rights reserved http://wwwcnkinet
48 2006 7 [5 ] PSO,, [6 Mauricec PSO ] Salman PSO [7 ], PSO [8 ], PSO [9 ],, 1 P D C, 1, I,,, (S - 1,S),,, 2 2 2,1,, : ( ) : min D I h di S di i = 1 P D p = 1 C + c c = 1 k pd c Y p( i) d i I p( i) = p D + d d P C + p = 1 D + dr k dr c = 1 k pc < I i = 1 w dri V p( i) c i I p( i) = p ri D + C D + q dr c = 1 I dr i = 1 ri, k cd U cdi + D s t V p( i) c = U cdi c = 1,2,, C i = 1,2,, I (1) Y p( i) d V p( i) c C + U cdi = c = 1 c di = dr S di = min S D N min d dr ri,2,, D i = 1,2,, I (2) ri c = 1,2,, C i = 1,2,, I (3) ri,2,, D i = 1,2,, I (4) S - 1 k = 0 e - di di ( k! di di ) k di,2,, D i = 1,2,, I (5) d,2,, (6) dr N max d,2,, D (7) c = {0,1} c = 1,2,, C (8) i I 1994-2006 China Academic Journal Electronic Publishing House All rights reserved http://wwwcnkinet
7 49 d = {0,1},2,, D (9) dr = {0,1},2,, D,2,, (10) Y p( i) d 0 U cdi 0 V p( i) c 0 c = 1,2,, C i = 1,2,, I,2,, D (11) : : p c d i r p ( i) p i : c d dr 0-1, 1 c d d r Y p( i) d i p d U cdi c d i V p( i) c i p c S di i d, (5) : k pd k pc k cd k dr p d p c c d d r ri r i w dri i d r c d c d di d h di i d q dr 0-1,1 r d V pci U cdi i I Y pdi i I p( i) = p < i I p( i) = p p c c d p d, (1) (2) (3), (4) (5) (6) (7), 2 D,n, i D X i = ( x i1, x i2,, x id ), i = 1,2,, n,x i, X i i D = ( v i1, v i2,, v id ) i V i = ( p i1, p i2,, p id ), P g = ( p g1, p g2,, p gd ), : v id ( t + 1) = wv id ( t) + c 1 rand () [ p id ( t) - x id ( t) ] + c 2 rand () [ p gd ( t) - x id ( t) ], (12) x id ( t + 1) = x id ( t) + v id ( t + 1), 1 i n 1 d D, (13), c 1, c 2 rand() [0,1 ] w, w (exploration), w (exploitation) x id [ - X max d, X max d ], v id [ - V max d, V max d ], () ( Global) (local),kennedy,ing Wheel Star, [10 ] PSO, 1994-2006 China Academic Journal Electronic Publishing House All rights reserved http://wwwcnkinet P i
50 2006 7 3 -, 2 NP,, -,,, - 2 311 2 Hall,, : 1) 3 2) 2 3) 4) 2 Hall 3, 5) 4), 6) 5), Hall 2, 7) 2 6) 4), 6), 3) 312,, + D C D 1994-2006 China Academic Journal Electronic Publishing House All rights reserved http://wwwcnkinet
7 51 4 X A X B, X A D, u d = ( Int (random(0, C) ),Int ( ),random( ) 0 C, X B, y r = Int (random(1, d) ), d X A, r d,3,5,10 : [2 0 1 0 2 2 3 3 1 3 2 1 2 1 3] :1 3 5 2 1 2 10 3 5,5 1 5 3 1 3 1 5 [ u 1,, u d,, u D y 1,, y r,, y ], X A X B, 4 (3) (6) (7), 313,, v id ( t + 1) = Int{ wv id ( t) + c 1 rand ( ) [ p id ( t) - x id ( t) ] + c 2 rand ( ) [ p gd ( t) - x id ( t) ]}, x id ( t + 1) = Int (andom(0, T) ) x id ( t + 1) > T, Abs[ x id ( t) + v id ( t + 1) ) ] x id ( t + 1) T : Int ( ) Abs ( ) X A, T C, andom(0, T) 0 C, T X A d,andom(1, T) 1 d w,: X B w = ( w int - w end ) ( S max - t)πs max + w end S max, w int, w end, :,, = 1 - e - t S max, :X B n X A d,d > n,x A ( d - n) d < n,x A ( n - d) 1 d 314 1 S max, PS, c 1 c 2, w int w end : 1) 2) X A 0 - C, X A d, X B 1 - d 3) V A ( - C,C),V B ( - d, d) 4),,,, 5) P i, P l P g 2, 1) = 50 %( S max - t)πs max 2, 1 1994-2006 China Academic Journal Electronic Publishing House All rights reserved http://wwwcnkinet
52 2006 7 2) 3), P i, P l P g 4 6 2 15, 2, 5, 70, 90 % 30 V f ( V) = 0136 + 019 e - 18 3 V 8500, 15 1 ( ) 2 (Π) C01 C02 P01 1800 720 P02 2100 1020 C01 C02 D01 D02 D03 D04 D05 D06 cost 8 7 5 12 14 10 12 8 15 9 3 ( ) D01 D02 D03 D04 D05 D06 P01 2100 2040 1900 600 820 800 P02 2400 2340 2200 300 1120 1100 C01 400 320 350 2800 1300 700 C02 1600 1480 1300 1720 120 200 4 (Π) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 P P01 4 4 0 3 1 1 2 2 3 2 2 1 3 1 2 P02 5 6 1 6 2 1 1 2 2 2 1 2 2 1 3 5 ( ) 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 D01 1180 1211 1115 148 1230 769 867 193 132 1130 229 54 36 45 1160 D02 23 1123 1023 73 146 1093 39 86 54 129 332 233 63 71 95 D03 1905 1985 1055 89 1045 810 738 35 105 980 120 136 146 165 1985 D04 65 30 1720 2610 1626 2060 1970 2685 2660 1798 2560 2750 2815 2760 89 D05 1120 1278 22 980 87 321 287 1080 1045 62 1020 2180 2210 2169 1199 D06 1400 1360 398 1017 396 23 67 769 1086 332 1043 1153 1198 1210 1376 JBuilder 9 0,Pentium 1 6G,512M, : n = 60, 4 w int = 0190, w end = 012, c1 = c2 = 1128 800 6 6,, 7 C02 D04 D05 D06, C02 D05 D06, D04, 413 D04 C02, D03,, 1994-2006 China Academic Journal Electronic Publishing House All rights reserved http://wwwcnkinet
7 53 6 XA :110222 XB :334245522421113 6291339 41 7 C01 C02 D01 D02 D04 D05 D06 12 13 14 04 11 08 09 01 02 15 05 03 10 07 06, 20,, 018, 0105, 60, 800 8 8 (s) () PSO 76 % 138 234 643 2 PSO 88 % 165 338 629 13 74 % 287 496 636 5 100 % 549 626 42 8, PSO,,,, PSO,,, ( ) 46, 90 % 5,,, : [ 1 ] Nozick L K, Turnquist M A Integrating inventory impacts into a fixed charge model for locating distribution centers [J ] Transportation esearch Part E, 1998, 43(3) :173-186 [ 2 ],, [J ],2004,19(1) :59-66 Tan Ling, GAO Junjun, WANG Yingjun Study on problem of distribution center location based on inventory cost optimization[j ] Chinese Journal of System Engineering, 2004, 19(1) : 59-66 [ 3 ] Hall W Direct versus terminal freight routing on a network with concave costs [J ] Transportation esearch Part B, 1987, 21 (4) :287-298 [ 4 ], GA [J ],2004,44(11) :1441-1444 Tian Qing, Miao Lixin, Zhang Li Logistics network design based on transport planning and combined GA[J ] Journal of Tsinghua University (Sci &Tech), 2004, 44(11) :1441-1444 [ 5 ] Kennedy J, Eberhart C Particle swarm optimization [A] IEEE Int Conf on Neural Networks[ C] Perth, 1995 1942-1948 ( 85 ) 1994-2006 China Academic Journal Electronic Publishing House All rights reserved http://wwwcnkinet
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