Y. Davidor, T. Yamada, and R. Nakano. The ECOlogical Framework II: Improving GA performance at virtually zero cost. In Proc. International Conf. on Genetic  Home/Search   Document Not in Database   Summary   Related Articles   Check

....1 Introduction It is well known that genetic algorithms (GAs) often converge to local optima before discovering a globally optimal solution. Much research has focused on the problem of preventing premature convergence, including various niching speciation mating neighborhood models (c.f. [4, 6, 3, 2, 5]) However, even when mechanisms for preventing premature convergence are implemented, extended runs of GAs still reach a point of significantly diminishing marginal return, i.e. convergence. Furthermore, for most real world problems, it is not possible to know whether a GA has found the global ....

Y. Davidor, T. Yamada, and R. Nakano. The ECOlogical Framework II: Improving GA performance at virtually zero cost. In Proc. International Conf. on Genetic

....Consequently, researchers have concentrated on developing algorithms that search through the vast state space of the problem in an efficient manner looking for near optimal solutions. Yamada and Nakano [15] developed a GA implementation for large scale job shop problems. Also, Davidor et al. [2] investigated GAs as a technique for solving the job shop scheduling problem. Kidwell [9] developed a GA to schedule distributed tasks on a bus based system. Li and Cheng [11] developed a job shop scheduling algorithm to partition a mesh connected system, where jobs require square meshes and the ....

Y. Davidor, T. Yamada, and R. Nakano. The ECOlogical framework II: Improving GA performance at virtually zero cost. In Forrest [3].

....multiprocessor scheduling problem and its variations of other scheduling problems are economically very important problems, especially in industrial applications. 21 For the interested reader, Yamada and Nakano [42] present a GA implementation for large scale job shop problems. Davidor et al. [13] investigated GAs as a technique for solving the job shop scheduling problem. Kidwell [26] developed a GA to schedule distributed tasks on a bus based system. Li and Cheng [28] developed a job shop scheduling algorithm to partition a mesh connected system where jobs require meshes an the system ....

Y. Davidor, T. Yamada, and R. Nakano. The ECOlogical framework II: Improving GA performance at virtually zero cost. In Forrest [18].

....[239, 280] Authors 15 Corwin, Edward M. 396] Crummey, T. P. 131] Crutch eld, James P. 12, 16, 20, 23, 41, 45, 46] Cui, Jun, 547, 399, 548, 400] Daemi, M. F. 13] D Agostino, G. 259, 325] Daley, M. L. 202, 382] D Antone, I. D. 86] Das, Rajarshi, 16, 20, 23] Davidor, Yuval, [211, 383] Davies, R. 161] Davis, Mike, 87] Dekker, Laura, 102] De Falco, Ivanoe, 167, 240, 276] De Jong, Kenneth A. 264] Della Cioppa, A. 167, 240, 276] Del Balio, R. 167, 240, 276] Del Carpio, Carlos A. 236] Dell Orto, Massimo, 82] Delport, V. 302] Derks, E. P. P. A. 231] Detitta, ....

....Heinz, 442, 76, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457] Muller, C. 473] Munetomo, M. 142] Muntean, Traian, 504, 508] Murthy, V. K. 182] Mutalik, Pooja P. 365] Nagano, Shinobu, 29] Nakagawa, A. 230] Nakanishi, Y. 281] Nakano, Ryohei, [383] Nakao, Zensho, 308, 309] Nang, Jongho, 113, 252, 458, 459] Napierala, G. 460] Navetta, Joseph, 83] Nelson, K. M. 60] N emec, Viktor, 538] Neri, Filippo, 212] Neuhaus, P. 461] Neves, J. 110, 183] Neves, N. 256] Nguyen, A. T. 256] Nishidate, Kazume, 27] Nishikawa, Yoshikawa, ....

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Yuval Davidor, Takeshi Yamada, and Ryohei Nakano. The ECOlogical framework II: Improving GA performance at virtually zero cost. In Forrest [560], pages 171-176. ga:Davidor93a.

....S. 912] Damper, R. 432] Dandy, Graeme C. 937, 939, 940, 941] D Anjou, A. 615] Darenfeld, S. 198] Das, Rajarshi, 1065] Dasgupta, Dipankar, 199, 200, 201, 704, 705, 706, 707, 708, 709] Dastidar, D. Ghosh, 202] David, E. 963] Authors 17 Davidge, Robert, 203] Davidor, Yuval, [204, 205] Davis, Lawrence, 206, 207, 208, 209, 210] Davis, Thomas Elder, 973] Deb, Kalyanmoy, 217, 375, 376, 378, 381] Deboeck, Guido, 218, 219] deFigueiredo, Rui J. P. 944] Delaney, B. 239] Denham, M. J. 797] Deodhar, D. 538] Deugo, Dwight, 220, 221] Dhawan, Atam P. 222, 223, 657, ....

....G. 157] Nafia, Mohammed, 742] Nagahashi, Hiroshi, 743, 744, 745, 746] Nagao, Tomoharu, 743, 744, 745, 746] Nagendra, Somanath, 416, 420] Naillon, Martine, 65] Nakagiri, Shigeru, 1080] Nakahashi, Hiroshi, 49] Nakanishi, Masakazu, 572] Nakanishi, Yasuhiko, 1080] Nakano, Ryohei, [204] Nakayama, Hirotaka, 747] Nakayama, T. 1024] Nambiar, R. 686] Nang, Jongho, 748, 749] Napliotis, Nicholas, 476] Nara, Koichi, 750] Narayanan, M. N. 881] Nelson, B. 954] Nettleton, David John, 751, 752, 774, 775] Newquist, III, Harvey P. 753] Ng, S. C. 754] Ngo, J. ....

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Yuval Davidor, T. Yamada, and Ryohei Nakano. The ECOlogical framework II: Improving GA performance at virtually zero cost. In Forrest [347], pages 171--176. ga:Davidor93a.

....Chew, W. C. 1016] Chiang, H. D. 351] Chiang, Hsaio Dong, 423, 481, 688] Chiang, Hsiao Dong, 124] Chiba, T. 472] Cho, B. J. 467] Cho, In Hyun, 1057] Cho, Sung Bae, 245] Choi, D. 181, 290, 420] Choy, O. C. 879] Cingoski, V. 804, 1206] Date, H. 573] Davidor, Yuval, [58, 1317] DeBaerdemaeker, J. 895] DelCarpio, Carlos A. 1058] De Garis, Hugo, 819] Del Carpio, Carlos A. 471] Del Carpio, Carlos Adriel, 1108] Deris, Safaai, 587, 1249] Doi, Hirofumi, 100, 122, 489, 1469] Dongyong, Yang, 968] Dote, Y. 970, 1199] Douzono, H. 1059, 1218, 1236, ....

....[941, 1034, 1565] Nakamura, Yoshiaki, 1207] Nakanishi, Masakazu, 210, 1391] Nakanishi, M. 253, 626, 1288] Nakanishi, S. 363, 923, 1009, 1436] Nakanishi, Yasuhiko, 1473] Nakanishi, Y. 688, 748] Nakano, H. 1545] Nakano, Kaoru, 144, 232] Nakano, R. 1556, 1213] Nakano, Ryohei, [58, 279, 667, 1317, 1420, 1421] Nakao, Taketoshi, 1294] Nakao, Zensho, 233, 364, 408, 419, 431, 439, 451, 566, 571, 658, 678, 677, 739, 744, 768, 771, 780, 782, 786, 791, 459, 964, 969, 989, 1023] Nakao, Z. 989, 1017, 1022, 1037, 1062, 1212, 1204] Nakaoka, K. 125, 188, 296, 570] Nakaoka, N. 157] Nakari, T. ....

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Yuval Davidor, Takeshi Yamada, and Ryohei Nakano. The ECOlogical framework II: Improving GA performance at virtually zero cost. In Forrest [1615], pages 171-176. ga:Davidor93a.

....with GSGAs, it is performed in the search space. When local selection is performed, it is performed in the population grid. Two general methods of local selection have been used to perform selection in GSGAs: 1) fixed size neighborhoods have been used to define the set of neighboring individuals [14, 35], and (2) random walks have been used to stochastically sample the locations of neighboring individuals [12, 56] Figure II.4 illustrates the fixed size neighborhoods that could be used to perform selection. Proportional selection is applied to the solutions in each of these neighborhoods. Since ....

....argued that the algorithmic nature of GSGAs may be of interest, independent from their implementation on a particular architecture. They experimentally compare GSGAs to panmictic GAs and observe that the GSGAs provide superior performance. This philosophy is echoed by Davidor, Yamada and Nakano [14] in their motivation for the ECO framework. The ECO framework provides a serial design for implementing a geographically structured GA. Finally, we note that our definition of GSGAs includes GAs which structure the selection at a fine granularity. A number of GAs have been proposed whose ....

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Yuval Davidor, Takeshi Yamada, and Ryohei Nakano. The ECOlogical framework II: Improving GA performance at virtually zero cost. In Stephanie Forrest, editor, Proceedings of the Fifth Intl. Conf. on Genetic Algorithms, pages 171-- 176. Morgan-Kaufmann, 1993.

....GAs with other existing complicated algorithms. For example, Yamada Nakano 92] hybridised [Giffler Thompson 60] s active scheduling algorithm with a GA which represented an individual directly from its operation completion times, improving on the solution quality of [Nakano 91] Later, Davidor et al. 93] further put their approach in Davidor s ECOlogical framework, and found that average solution quality improved further without additional computational cost. Croce et al. 92] used a multi permutation sequence, one for each machine, and a schedule generation algorithm to specify the job ....

Yuval Davidor, Takeshi Yamada, and Ryohei Nakano. The ECOlogical framework II: Improving GA performance at virtually zero cost. In Stephanie Forrest, editor, Proceedings of the Fifth International Conference on Genetic Algorithms, pages 171--176. San Mateo: Morgan Kaufmann, 1993.

....is widely studied in the field of management science. It is a notoriously difficult NP complete problem [13] that is hard to solve even for small instances. A great deal of effort over the course of thirty years has gone into finding efficient approximation algorithms for it. See, for example, [4, 5, 7, 24, 6, 28, 9, 27]. In this problem, a collection of J jobs are to be scheduled on M machines (or processors) each of which can process only one task at a time. Each job is a list of M tasks which must be performed in order. Each task must be performed on a specific machine, and no two tasks in a given job are ....

....of research has also been invested in the similarly challenging 20x5 problem, for which an optimal value of 1165 has been achieved, and a lower bound of 1164 [6] A number of papers have considered the application of GAs to scheduling problems. In particular, Nakano and Yamada [28] Davidor et al. [7], and Fang et al. 9] have described GAs designed to address the three benchmark instances for the jobshop problem. We compare our results with those obtained in Fang et al. one of the more recent of these articles. The GA Fang et al. encode a jobshop schedule in the form of a string of ....

Y. Davidor, T. Yamada, and R. Nakano. The ECOlogical framework II: Improving GA performance at virtually zero cost. In Forrest, editor, Proceedings of the Fifth International Conference on Genetic Algorithms, pages 171--176, San Mateo, CA, 1993. Morgan Kaufmann.

....to reveal such pronounced benefits of pGAs in comparison to traditional GAs. Nonetheless, pGAs have shown benefits in a large number of optimization problems, both in terms of the number of evaluations performed and the final results obtained [Husbands, 1990] Whitley Starkweather, 1990] [Davidor et al. 1993] [Gordon Whitley, 1993] The previous paragraphs showed that a simple genetic algorithm, with a single population, cannot maintain dissimilar points in the function space. The Fundamental Theorem of Genetic Algorithms does not address this. This theorem is stated below: Short, low order, ....

Davidor, Y., Yamada, T. & Nakano, R. (1993) "The ECOlogical Framework II: Improving GA Performance At Virtually Zero Cost". In Forrest (ed). Proceedings of the Fifth International Conference on Genetic Algorithms. 171 - 176. Morgan Kaufmann Publishers. San Mateo, CA.

....that directly utilizes the GT algorithm. In the crossover, parents cooperatively give a series of decisions to the algorithm to build new o#spring, namely active schedules. An individual represents an active schedule, so there is no repairing scheme required. Let H be a binary matrix of size n m [24, 8]. Here H ir = 0 means that the i th operation on machine r should be determined by using the first parent and H ir = 1 by the second parent. The role of H ir is similar to that of h described in Section 3.2. Let the parent schedules be p 0 and p 1 as always. The GT crossover can be defined by ....

Y. Davidor, T. Yamada, and R. Nakano (1993). The ecological framework II: Improving GA performance at virtually zero cost. In 5th ICGA, pages 171--176.

....GT algorithm. In the crossover, parents cooperatively give a series of decisions to the algorithm to build new offsprings, namely active schedules. An individual represents an active schedule, so there is no repairing scheme required. 7.5. 1 GT crossover Let H be a binary matrix of size n m [30, 10]. Here H ir = 0 means that the i th operation on machine r should be determined by using the first parent and H ir = 1 by the second parent. The role of H ir is similar to that of h described in Section 7.4.2. Let the parent schedules be p 0 and p 1 as always. The GT crossover CHAPTER 7. JOB SHOP ....

Y. Davidor, T. Yamada, and R. Nakano. The ecological framework II: Improving GA performance at virtually zero cost. In 5th ICGA, pages 171--176, 1993.

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Davidor, Y., Yamada, T., and Nakano, R., (1993), "The ecological framework II: improving GA performance at virtually zero cost", ICGA'5 5th International Conference on Genetic Algorithms, 171-176.

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Davidor, Y., Yamada, T. and Nakano, R. (1993) The Ecological Framework II: Improving GA Performance at Virtually Zero Cost, ICGA'5 5th International Conference on Genetic Algorithms, pp. 171-176.

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