G. Syswerda and J. Palmucci, "The Application of Genetic Algorithms to Resource Scheduling," Proceedings of the Fourth International Conference on Genetic Algorithms, University of California, San Diego, Richard K. Belew and Lashon B. Booker, editors, pages 502-508, 13-16 July 1991.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....problem solving strategy, based loosely on Darwinian evolution, that has been successfully used for a large number of scheduling and optimization In X. Yao (Editor) Proceedings of The Australia Japan Joint Workshop on Intelligent and Evolutionary Systems , Pages 55 64, Canberra, 1997 problems[2, 9]. Genetic algorithms are generally associated with long computation times and great uncertainty about how long a computation will take. Consequently they are not normally considered for real time problems, such as the optimal scheduling of aircraft landing times. Despite the perceived ....

G. Syswerda and J. Palmucci. The application of genetic algorithms to resource scheduling. In Proceedings of the Fourth International Conference on Genetic Algorithms, pages 502--508, University of California, San Diego, 1991.

.... N eanmoins, cette approche a largement et e utilis ee dans la litt erature a l aide de diff erentes m etaheuristiques : ffl Algorithmes g en etiques : les algorithmes g en etiques ont et e utilis es pour r esoudre plusieurs PMO transform es en un probl eme uni objectif : ordonnancement [83], planification de robots [44] g en eration de structures chimiques [46] conception de filtres IIR [99] placement [49] transport [100] En plus de la repr esentation d une solution du probl eme dans le codage d un individu, Hajela et Lin [35] ont inclu les poids de chaque objectif dans les ....

G. Syswerda and J. Palmucci. The application of genetic algorithms to resource scheduling. In R. K. Belew and L. B. Booker, editors, Fourth Int. Conf. on Genetic Algorithms ICGA'4, pages 502--508, San Mateo, California, 1991. Morgan Kaufmann Pub.

....E. 213, 287, 289] Nyongesa, H. Okola, 95] Oba, F. 73] Okutani, I. 121] Onder, H. H. 57] Ono, Isao, 158] Oommen, B. J. 55, 56] Opaterny, Thilo, 60] Ost, Alexander, 60] Oyman, A. Iirfan, 25] Pakath, Ramakrishnan, 206] Palmer, Mark R. 221, 222, 223, 224] Palmucci, Jeff, [250] Pao, Yoh Han, 135, 68] Paredis, Jan, 234, 235] Parsaei, Hamid R. 86] Parsons, Rebecca, 271, 272] Perkins, Sonya, 167] Perov, V. L. 171] Pesch, Erwin, 236] Pettey, Chrisila C. 159] Pham, D. T. 57] Pico, Carlos Alberto Gonzalez, 133] Pingfan, Yan, 154] Prosser, P. 281, ....

....Sridhar, J. 137] Sridharan, V. 214, 215] Stadler, W. 78] Starkweather, Timothy John, 275, 248, 261, 262, 263] Stefanitsis, E. 163] Stoppler, S. 179] Storer, Robert H. 125] Sugai, Y. 42, 43, 44] Suginohara, N. 242] Sutoh, T. 138] Suzuki, H. 138] Syswerda, Gilbert, [249, 250, 251] Takai, Yoshiaki, 130] Talbi, El Ghazali, 253, 254] Tam, Kar Yan, 62, 63] Tamaki, Hisashi, 255, 256, 257, 258] Tan, C. Y. 115, 140] Taneja, Mukesh, 74] Tansri, H. 23, 64] Tate, David M. 65] Tenga, R. F. 87] Thangiah, Sam Rabindranath, 287, 288, 289] Tokumaru, H. 80] ....

[Article contains additional citation context not shown here]

Gilbert Syswerda and Jeff Palmucci. The application of genetic algorithms to resource scheduling. In Belew and Booker [298], pages 502--508. ga:Syswerda91a.

....permutation and swaps their positions. Genetic and evolutionary algorithms have been applied to a variety of scheduling problems, including flowshop [23] 4] and jobshop [7] 1] 9] 14] problems, timetabling problems [11] 6] as well as to a variety of dynamic and real world applications (e.g. [28], 24] 10] A survey of this literature is given by Hart and Corne [13] Finally, hybrid algorithms seek to achieve the benefits of both types of algorithms by combining the search algorithms with the domain specific knowledge. Our results suggest that this hybrid approach provides the best ....

Gilbert Syswerda and Jeff Palmucci. The Application of Genetic Algorithms to Resource Scheduling. In L. Booker and R. Belew, editors, Proc. of the 4th Int'l. Conf. on GAs. Morgan Kaufmann, 1991.

....was first investigated by Davis [4] in the mid 1980 s. He successfully optimised a simplified job shop scheduling problem with a single criterion. Since then there have been many other attempts at problems such as job shop (Bruns [5] Cheng [6] Fang [7] Gen [8] Nakano [9] Reeves [10] Syswerda [11]) flowshop (Cleveland [12] line balancing (Anderson [13] Kim [14] and resource allocation (Easton [15] Tanomaru [16] in different domains. More complex approaches by Liang [17] and Sridhar [18] use a weighted sum approach to combine disparate metrics to give a single fitness measure. Murata ....

Syswerda, G. and Palmucci, J., The Application of Genetic Algorithms to Resource Scheduling, Proceedings of the Forth International Conference on Genetic Algorithms, pp502-508, Morgan Kaufmann Publishers, 1991.

....c i are constant multipliers that will scale properly the objectives. The best results are usually obtained if c i = 1=f 0 i . In this case, the vector function is normalized to the form f(x) f 1 (x) f 2 (x) f k (x) T , where f i (x) f i (x) f 0 i . Applications Syswerda and Palmucci [1991] used weights in their fitness function to add or subtract values during the schedule evaluation of a resource scheduler, depending on the existence or absence of penalties (constraints violated) Jakob et al. 1992] used a weighted sum of the several objectives involved in a task planning ....

Syswerda, G. and Palmucci, J. 1991. The Application of Genetic Algorithms to Resource Scheduling. In R. K. Belew and L. B. Booker Eds., Proceedings of the Fourth International Conference on Genetic Algorithms (San Mateo, California, 1991), pp. 502--508. Morgan Kaufmann.

....operators cannot necessarily generate a solution in S from every state in S. Examples of EAs that satisfy Assumption 3 are many of the GAs used to search through the space of permutations. These EAs have been applied problems such as the travelling salesman problem [22, 27] scheduling problems [22, 24], the clustering problem [3] and partitioning problems [15] The limitation of the evolutionary operators for these EAs lies in the fact that the mutation operator is typically an operation like two opt, which generates a small number of possible neighbors. 6 Discussion Note that the analysis ....

G. Syswerda and J. Palmucci, The application of genetic algorithms to resource scheduling, in Proc. of the 4th Intl. Conf. on Genetic Algorithms, R. K. Belew and L. B. Booker, eds., Morgan Kaufmann, 1991, pp. 502--508.

....i ( x) 6) where w i 0 are the weighting coefficients representing the relative importance of the objectives. It is usually assumed that k X i=1 w i = 1 (7) 2 The interested reader should refer to [4, 5] for more detailed surveys of EMOO approaches. 4.1. 1 Applications Syswerda and Palmucci [6] used weights in their fitness function to add or subtract values during the schedule evaluation of a resource scheduler, depending on the existence or absence of penalties (constraints violated) Jakob et al. 7] used a weighted sum of the several objectives involved in a task planning problem : ....

Gilbert Syswerda and Jeff Palmucci. The Application of Genetic Algorithms to Resource Scheduling. In Richard K. Belew and Lashon B. Booker, editors, Proceedings of the Fourth International Conference on Genetic Algorithms, pages 502--508, San Mateo, California, 1991. Morgan Kaufmann.

....d[i] predicted frame Figure 16. Behavioral specification of a video codec for video compression. the lists (repair allocation priority lists L Ri , binding order lists LOi and the binding priority lists LBi (v) order based crossover (also named position based crossover) is applied (see e.g. [22, 10]) Order based crossover ensures that only permutations of the elements in the chromosomes are created, i.e. parts of the list of the parents are combined and repaired such that a legal permutation is obtained. The probability of crossover is 50 . The construction of the individuals makes further ....

G. Syswerda and J. Palmucci. The application of genetic algorithms to resource scheduling. In R.K. Belew and L.B. Booker, editors, Proceedings of the Fourth International Conference on Genetic Algorithms, pages 502--508, San Mateo, CA, 1991. Morgan Kaufmann Publishers.

....degraded when applied to more typical scheduling problems. Starkweather et al. 91] compare six sequencing operators for TSP and scheduling problems and conclude that the results of schedule optimisation were almost the opposite of the results from the TSP. These differences 3 [Syswerda 91, Syswerda Palmucci 91] showed how a JSSP may be represented in a way similar to the TSP with operators to guarantee legal solutions. CHAPTER 2. LITERATURE REVIEW IN TIMETABLING SCHEDULING 23 can be explained by examining how these operators preserve adjacency (for the TSP) and order information (for the scheduling) ....

G. Syswerda and J. Palmucci. The application of genetic algorithms to resource scheduling. In R.K. Belew and L.B. Booker, editors, Proceedings of the Fourth International Conference on Genetic Algorithms, pages 502--508. San Mateo: Morgan Kaufmann, 1991.

....at any time and will always have a result available but will produce a better result given more time. Genetic algorithms[2] 3] are a problem solving strategy, based loosely on Darwinian evolution, that has been successfully used for a large number of scheduling and optimization problems[4] [5]. Genetic algorithms are generally associated with long computation times and great uncertainty about how long a computation will take. Consequently they are not normally considered for real time problems, such as the optimal scheduling of aircraft landing times. Despite the perceived ....

G. Syswerda and J. Palmucci, "The application of genetic algorithms to resource scheduling," in Proceedings of the Fourth International Conference on Genetic Algorithms, (University of California, San Diego), pp. 502--508, 1991.

.... for the allocations ff i uniform crossover was used [ Syswerda, 1989 ] whereas for the several lists (repair allocation priority lists LR , binding order lists LO and the binding priority lists LB (v) order based crossover (also names position based crossover) is applied (see, e.g. Syswerda and Palmucci, 1991; Fox and McMahon, 1991 ] The probability of crossover is of 90 and due to the construction of the individuals no special repairing methods are necessary. Mutation is used with a probability of 10 . The expected run time of the optimization procedure for design space exploration is ....

Gilbert Syswerda and Jeff Palmucci. The application of genetic algorithms to resource scheduling. In R.K. Belew and L.B. Booker, editors, Proceedings of the Fourth International Conference on Genetic Algorithms, pages 502--508, San Mateo, CA, 1991. Morgan Kaufmann Publishers.

....to attain a local optimum. See also Syswerda and Palmucci s work in this Frequency Assignment Problem Convoy Routing Traffic Routing in Telecommunications GAs GA Frequency Assignment Problem Convoy Movement Problem branch and bound branch and bound GA branch and bound GAs GA GA GA area [23]. Both these ideas, i.e. the use of local optimisers, and using at a meta level, have been incorporated into the current study. Bloemen [24] has described a mathematical formulation of the frequency assignment problem (FAP) of a mobile communications network, and shows how the decision variant of ....

G. Syswerda and J. Palmucci. The application of genetic algorithms to resource scheduling. In R.K. Belew and L.B. Booker, editors,

....chromosome into a schedule ready for evaluation provides a key part of fitness assignment and thus performance of the GA. Detailed descriptions of schedule builder implementations may be found in several sources developing from the initial suggestion by Davis, 1985) e.g. Whitley, et al. 1989) Syswerda and Palmucci, 1991) Syswerda, 1991) Bagchi et al. 1991. Which Line is It Anyway Use of Rules and Preferences for Schedule Builders in Genetic Algorithms for Production Scheduling K.J. Shaw and P.J. Fleming ....

....for evaluation provides a key part of fitness assignment and thus performance of the GA. Detailed descriptions of schedule builder implementations may be found in several sources developing from the initial suggestion by Davis, 1985) e.g. Whitley, et al. 1989) Syswerda and Palmucci, 1991) Syswerda, 1991), Bagchi et al. 1991. Which Line is It Anyway Use of Rules and Preferences for Schedule Builders in Genetic Algorithms for Production Scheduling K.J. Shaw and P.J. Fleming ....

Syswerda and Palmucci, 1991. The Application of Genetic Algorithms to Resource Scheduling,. Proceedings of the Fourth International Conference on Genetic Algorithms, pp. 502 - 508.

....of optimisation, and has become something of a benchmark for optimisation algorithms. ffl Learning routes and schedules [8] This problem involved the GA having to route and schedule trains in a rail network. This approach was shown to be useful, as well as feasible. ffl Resource scheduling [23]. Syswerda and Palmucci were faced with the problem of scheduling the use of a flight simulator equipment. They demonstrated how a general evolutionary approach could give good results, quickly while improving it s performance if given more time. 2.3 Background in Scheduling with Genetic ....

G. Syswerda and J. Palmucci. The application of genetic algorithms to resource scheduling. In Proceedings of the Fourth International Conference on Genetic Algorithms, pages 502--508, University of California, San Diego, 1991.

....inappropriate setting of the coefficients of the combining function, new runs of the optimizer may be required until a suitable solution is found. Several applications of evolutionary algorithms in the optimization of aggregating functions have been reported in the literature. A number of authors (Syswerda and Palmucci, 1991; Jakob et al. 1992; Jones et al. 1993) provide examples of the use of the popular weighted sum approach. Using target vector optimization, which consists of minimizing the distance in objective space to a given goal vector, Wienke et al. 1992) report work on a problem in atomic emission ....

Syswerda, G. and Palmucci, J. (1991). The application of genetic algorithms to resource scheduling. In (Belew and Booker, 1991), pages 502--508.

....algorithms have proven themselves useful in a variety of optimization problems and have been given praise for their ease of implementation and near optimal solutions. Genetic algorithms have been very successful in a variety of scheduling problems where optimal solutions are too costly to produce [11, 12, 15, 16]. 4.1 Overview of Genetic Algorithms Our genetic algorithm models consist of a population of strings called chromosomes C, an evaluation function called a fitness function E(C) and a life cycle consisting of three operators: reproduction, 0 0 0 1 1 0 0 (5) 0 0 0 0 1 0 1 (2) 1 0 0 0 0 1 0 ....

G. Syswerda and J. Palmucci. The application of genetic algorithms to resource scheduling. In Proceedings of the Fourth International Conference on Genetic Algorithms, pages 502--508, July 1991.

....1.2 Background Existing literature seems to approach this ranking problem using methods that can be classified in one of three ways: the aggregating approaches, the non Pareto approaches and the Pareto approaches. Many examples of aggregation approaches exist, from simple weighting and summing (Syswerda and Palmucci, 1991; Goldberg 1989) to the multiple attribute utility analysis (MAUA) of Horn and Nafpliotis (1993) Of the non Pareto approaches, perhaps the most well known is Schaffer s VEGA (Schaffer 1984, 1985) who (as identified by Fonseca and Fleming, 1995a) does not directly make use of the actual ....

Syswerda, G. & Palmucci, J. (1991). The Application of Genetic Algorithms to Resource Scheduling.

....consid erer diff erents objectifs et contraintes r egissant l utilisation de ressources suppl ementaires. Sauf exception [49, 7] on utilise dans la plupart des cas un codage sous forme de permutation avec des op erateurs g en etiques adapt es. Parmi la litt erature abondante sur ce sujet, notons [2, 7, 10, 13, 40, 49, 54, 55, 60, 64]. 3.2.4 Coloration de graphe En plus des permutations, on retrouve maintenant une grande vari et e de m ethodes de codage pour les solutions. Pour un graphe G = V; E) un coloriage est une partition de V en k sous ensembles (couleurs) C 1 ; C 2 ; C k pour lesquels u; v 2 C i ) u; v) 2 ....

G. Syswerda et J. Palmucci, The Application of Genetic Algorithms to Resource Scheduling, Proceedings of the Fourth International Conference on Genetic Algorithms, San Mateo, Calif., Morgan Kaufmann Publishers, 1991, p. 502--507.

....will scale properly the objectives. The best results are usually obtained if c i = 1=f 0 i . In this case, the vector function is normalized to the form f( x) f 1 ( x) f 2 ( x) f k ( x) T , where f i ( x) f i ( x) f 0 i . Applications Syswerda and Palmucci [90] used weights in their fitness function to add or subtract values during the schedule evaluation of a resource scheduler, depending on the existence or absence of penalties (constraints violated) Jakob et al. 41] used a weighted sum of the several objectives involved in a task planning ....

Gilbert Syswerda and Jeff Palmucci. The Application of Genetic Algorithms to Resource Scheduling. In Richard K. Belew and Lashon B. Booker, editors, Proceedings of the Fourth International Conference on Genetic Algorithms, pages 502--508, San Mateo, California, 1991. Morgan Kaufmann.

....an important group of approximate methods. There are many publications devoted to genetic algorithm (GA) applications to scheduling problems see, for example, review work [1] Some papers include information about GA applications to scheduling in aircraft design [2] resource distribution [3], manufacturing processes [4] frequency assignment in radio channels of networks [5] etc. One of the main tasks in scheduling by GA is the formulation of the chromosome structure, i.e. the representation of the data about work distribution in time and between servers to be used by the GA. It ....

Syswerda, G., Palmucci J., 1991, The application of genetic algorithms to resource scheduling, Proc. of fourth int. conf. on GA, pp. 502-508.

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G. Syswerda and J. Palmucci, "The Application of Genetic Algorithms to Resource Scheduling," Proceedings of the Fourth International Conference on Genetic Algorithms, University of California, San Diego, Richard K. Belew and Lashon B. Booker, editors, pages 502-508, 13-16 July 1991.

No context found.

G. Syswerda, J. Palmucci. "The Application of Genetic Algorithms to Resource Scheduling". In Proceedings of the Fourth International Conference on Genetic Algorithms, San Mateo, California, 1991, 502-508. 246

No context found.

REFERENCES 171 Syswerda, G. and Palmucci, J. (1991). The application of genetic algorithms to resource scheduling. In (Belew and Booker, 1991), pages 502--508.

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Syswerda G, Palmucci J, 1991. The Application of Genetic Algorithms to Resource Scheduling. Proceedings of the Forth International Conference on Genetic Algorithms. Morgan Kaufmann Publishers, pp502-508.

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