nach oben

Journal of Intelligent Manufacturing

Erschienen in:

30.11.2013

Swarm lexicographic goal programming for fuzzy open shop scheduling

verfasst von: Juan José Palacios, Inés González-Rodríguez, Camino R. Vela, Jorge Puente

Erschienen in: Journal of Intelligent Manufacturing | Ausgabe 6/2015

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

In this work we consider a multiobjective open shop scheduling problem with uncertain processing times and flexible due dates, both modelled using fuzzy sets. We adopt a goal programming model based on lexicographic multiobjective optimisation of both makespan and due-date satisfaction and propose a particle swarm algorithm to solve the resulting problem. We present experimental results which show that this multiobjective approach achieves as good results as single-objective algorithms for the objective with the highest priority, while greatly improving on the second objective.

Vorheriger Artikel Failure time prediction for mechanical device based on the degradation sequence

Nächster Artikel A rule-based system for trade-off among energy consumption, tool life, and productivity in machining process

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Alcaide, D., Rodriguez-Gonzalez, A., & Sicilia, J. (2006). A heuristic approach to minimize expected makespan in open shops subject to stochastic processing times and failures. International Journal of Flexible Manufacturing Systems, 17, 201–226.CrossRefMATH

Andresen, M., Bräsel, H., Mörig, M., Tusch, J., Werner, F., & Willenius, P. (2008). Simulated annealing and genetic algorithms for minimizing mean flow time in an open shop. Mathematical and Computer Modelling, 48, 1279–1293.MathSciNetCrossRefMATH

Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17(4), 141–164.MathSciNetCrossRef

Belmecheri, F., Prins, C., & Yalaoui, F. L. A. (2013). Particle swarm optimization algorithm for a vehicle routing problem with heterogeneous fleet, mixed backhauls, and time windows. Journal of Intelligent Manufacturing, 24(4), 775–789.CrossRef

Blum, C. (2005). Beam-ACO—hybridizing ant colony optimization with beam search: An application to open shop scheduling. Computers & Operations Research, 32(6), 1565–1591.CrossRef

Bouveret, S., & Lemaître, M. (2009). Computing leximin-optimal solutions in constraint networks. Artificial Intelligence, 173, 343–364.

Brucker, P., Hunrink, J., Jurisch, B., & Wöstmann, B. (1997). A branch & bound algorithm for the open-shop problem. Discrete Applied Mathematics, 76, 43–59.MathSciNetCrossRefMATH

Celano, G., Costa, A., & Fichera, S. (2003). An evolutionary algorithm for pure fuzzy flowshop scheduling problems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11, 655–669.MathSciNetCrossRefMATH

Chen, S. M., & Chang, T. H. (2001). Finding multiple possible critical paths using fuzzy PERT. IEEE Transactions on Systems, Man, and Cybernetics-Part B, 31(6), 930–937.CrossRef

Coshall, J. T., & Charlesworth, R. (2011). A management orientated approach to combination forecasting of tourism demand. Tourism Management, 32, 759–769.CrossRef

Diaz-Balteiro, L., & Romero, C. (2008). Making forestry decisions with multiple criteria: A review and an assessment. Forest Ecology and Management, 255, 3222–3241.CrossRef

Dubois, D. (2011). The role of fuzzy sets in decision sciences: Old techniques and new directions. Fuzzy Sets and Systems, 184, 3–28.

Dubois, D., & Prade, H. (1986). Possibility theory: An approach to computerized processing of uncertainty. New York, NY, USA: Plenum Press.

Dubois, D., Fargier, H., & Prade, H. (1995). Fuzzy constraints in job-shop scheduling. Journal of Intelligent Manufacturing, 6, 215–234.

Dubois, D., Fargier, H., & Fortemps, P. (2003). Fuzzy scheduling: Modelling flexible constraints vs. coping with incomplete knowledge. European Journal of Operational Research, 147, 231–252.MathSciNetCrossRefMATH

Ehrgott, M. (2005). Multicriteria optimization (2nd ed.). Berlin: Springer.MATH

Ehrgott, M., & Gandibleux, X. (2000). A survey and annotated bibliography of multiobjective combinatorial optimization. OR Spektrum, 22, 425–460.MathSciNetCrossRefMATH

Farahani, R. Z., SteadieSeifi, M., & Asgari, N. (2010). Multiple criteria facility location problems: A survey. Applied Mathematical Modelling, 34, 1689–1709.MathSciNetCrossRefMATH

Fortemps, P. (1997). Jobshop scheduling with imprecise durations: A fuzzy approach. IEEE Transactions of Fuzzy Systems, 7, 557–569.CrossRef

Giffler, B., & Thompson, G. L. (1960). Algorithms for solving production scheduling problems. Operations Research, 8, 487–503.MathSciNetCrossRefMATH

Gonçalves, J., Magalhaes Mendes, J. J., & Resende, M. G. C. (2005). A hybrid genetic algorithm for the job shop scheduling problem. European Journal of Operational Research, 167, 77–95.

González Rodríguez, I., Puente, J., Vela, C. R., & Varela, R. (2008). Semantics of schedules for the fuzzy job shop problem. IEEE Transactions on Systems, Man and Cybernetics, Part A, 38(3), 655–666.CrossRef

González-Rodríguez, I., Palacios, J.J., Vela, C.R., & Puente, J. (2010). Heuristic local search for fuzzy open shop scheduling. In: Proceedings IEEE international conference on fuzzy systems, FUZZ-IEEE2010 (pp. 1858–1865). IEEE.

González Rodríguez, I., Vela, C. R., & Puente, J. (2010). A genetic solution based on lexicographical goal programming for a multiobjective job shop with uncertainty. Journal of Intelligent Manufacturing, 21, 65–73.CrossRef

Graham, R., Lawler, E., & Lenstra, J. (1979). Optimization and approximation in deterministic sequencing and scheduling: A survey. Annals of Discrete Mathematics, 4, 287–326.MathSciNetCrossRef

Guéret, C., & Prins, C. (1998). Classical and new heuristics for the open-shop problem: A computational evaluation. European Journal of Operational Research, 107, 306–314.CrossRefMATH

Guiffrida, A. L., & Nagi, R. (1998). Fuzzy set theory applications in production management research: A literature survey. Journal of Intelligent Manufacturing, 9, 39–56.CrossRef

Herroelen, W., & Leus, R. (2005). Project scheduling under uncertainty: Survey and research potentials. European Journal of Operational Research, 165, 289–306.CrossRefMATH

Hu, X., Eberhart, R.C., & Shi, Y. (2003). Swarm intelligence for permutation optimization: A case study of n-queens problem. In: Swarm intelligence symposium, 2003. SIS’03. Proceedings of the 2003 IEEE (pp. 243–246). IEEE.

Jia, Q., & Seo, Y. (2013). An improved particle swarm optimization for the resource-constrained project scheduling problem. International Journal of Advanced Manufacturing Technology , 67(9–12), 2627–2638.

Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. IEEE international conference on neural networks (pp. 1942–1948). New Jersey: IEEE Press.

Kim, B. I., & Son, S. J. (2012). A probability matrix based particle swarm optimization for the capacitated vehicle routing problem. Journal of Intelligent Manufacturing, 23, 1119–1126.CrossRef

Lei, D. (2008). Pareto archive particle swarm optimization for multi-objective fuzzy job shop scheduling problems. International Journal of Advanced Manufacturing Technology, 37, 157–165.CrossRef

Liaw, C. F. (1999). A tabu search algorithm for the open shop scheduling problem. Computers and Operations Research, 26, 109–126.MathSciNetCrossRefMATHADS

Liaw, C. F. (2000). A hybrid genetic algorithm for the open shop scheduling problem. European Journal of Operational Research, 124, 28–42.MathSciNetCrossRefMATH

Liberatore, F., Ortuño, M.T., Tirado, G., Vitoriano, B., & Scaparra, M. P. (2014). A hierarchical compromise model for the joint optimization of recovery operations and distribution of emergency goods in humanitarian logistics. Computers & Operations Research, 42, 3–13.

Liu, B., & Liu, Y. K. (2002). Expected value of fuzzy variable and fuzzy expected value models. IEEE Transactions on Fuzzy Systems, 10, 445–450.CrossRef

Marinakis, Y., & Marinaki, M. (2013). Particle swarm optimization with expanding neighborhood topology for the permutation flowshop scheduling problem. Soft Computing, 17(7), 1159–1173.CrossRef

Naderi, B., Fatemi Ghomi, S. M. T., Aminnayeri, M., & Zandieh, M. (2011). A study on open shop scheduling to minimise total tardiness. International Journal of Production Research, 49(15), 4657–4678.

Niu, Q., Jiao, B., & Gu, X. (2008). Particle swarm optimization combined with genetic operators for job shop scheduling problem with fuzzy processing time. Applied Mathematics and Computation, 205, 148–158.MathSciNetCrossRefMATH

Noori-Darvish, S., Mahdavi, I., & Mahdavi-Amiri, N. (2012). A bi-objective possibilistic programming model for open shop scheduling problems with sequence-dependent setup times, fuzzy processing times, and fuzzy due-dates. Applied Soft Computing, 12, 1399–1416.CrossRef

Palacios, J.J., González-Rodríguez, I., Vela, C.R., & Puente, J. (2011). Particle swarm optimisation for open shop problems with fuzzy durations. In: Proceedings of IWINAC 2011, Part I, Springer, Lecture Notes in Computer Science (Vol. 6686, pp. 362–371).

Panahi, H., Rabbani, M., & Tavakkoli-Moghaddam, R. (2008). Solving an open shop scheduling problem by a novel hybrid multi-objective ant colony optimization. In: Eighth international conference on hybrid intelligent systems (pp. 320–325). IEEE.

Pasandideh, S. H. R., Niaki, S. T. A., & Hajipour, V. (2013). A multi-objective facility location model with batch arrivals: two parameter-tuned meta-heuristic algorithms. Journal of Intelligent Manufacturing, 24(2), 331–348.

Petrovic, S., Fayad, S., & Petrovic, D. (2008). Sensitivity analysis of a fuzzy multiobjective scheduling problem. International Journal of Production Research, 46(12), 3327–3344.CrossRefMATH

Pinedo, M. L. (2008). Scheduling, theory, algorithms, and systems (3rd ed.). Berlin: Springer.MATH

Prins, C. (2000). Competitive genetic algorithms for the open-shop scheduling problem. Mathematical Methods of Operations Research, 52, 389–411.MathSciNetCrossRefMATH

Puente, J., Vela, C. R., & González-Rodríguez, I. (2010). Fast local search for fuzzy job shop scheduling. In: Proceedings of ECAI 2010 (pp. 739–744). IOS Press.

Puente, J., Vela, C. R., González-Rodríguez, I., Rodríguez, L. J., & Palacios, J. J. (2013). GRASPing examination board assignments for university-entrance exams. In: IEA-AIE 2013, Proceedings of, Springer, Lecture notes in computer science (Vol 7906, pp. 171–180).

Romero, C. (2001). Extended lexicographic goal programming: a unifying approach. Omega, 29, 63–71.CrossRef

Sakawa, M., & Kubota, R. (2000). Fuzzy programming for multiobjective job shop scheduling with fuzzy processing time and fuzzy duedate through genetic algorithms. European Journal of Operational Research, 120, 393–407.MathSciNetCrossRefMATH

Sha, D., Lin, H. H., & Hsu, C. (2010). A modified particle swarm optimization for multi-objective open shop scheduling. In: Proceeding of the international multiconference of engineers and computer scientists, Vol 3.

Sha, D. Y., & Cheng-Yu, H. (2008). A new particle swarm optimization for the open shop scheduling problem. Computers & Operations Research, 35, 3243–3261.CrossRefMATH

Tamiz, M., Jones, D., & Romero, C. (1998). Goal programming for decision making: An overview of the current state-of-the-art. European Journal of Operations Research, 111, 569–581.CrossRefMATH

Tassopoulos, I. X., & Beligiannis, G. N. (2012). Using particle swarm optimization to solve effectively the school timetabling problem. Soft Computing, 16, 1229–1252.CrossRef

T’kindt, V., & Billaut, J. C. (2006). Multicriteria scheduling. Theory, models and algorithms (2nd ed.). Berlin: Springer.MATH

Vijay Chakaravarthy, G., Marimuthu, S., & Naveen Sait, A. (2013). Performance evaluation of proposed differential evolution and particle swarm optimization algorithms for scheduling m-machine flow shops with lot streaming. Journal of Intelligent Manufacturing, 24, 175–191.CrossRef

Wang, L., Zhou, G., Xu, Y., & Min, L. (2013). A hybrid artificial bee colony algorithm for the fuzzy flexible job-shop scheduling problem. International Journal of Production Research, 51(2), 3593–3608.

Zheng, Y., Li, Y., & Lei, D. (2011). Swarm-based neighbourhood search for fuzzy job shop scheduling. International Journal of Innovative Computing and Applications, 3(3), 144–151.CrossRef

Titel: Swarm lexicographic goal programming for fuzzy open shop scheduling
verfasst von: Juan José Palacios
Inés González-Rodríguez
Camino R. Vela
Jorge Puente
Publikationsdatum: 30.11.2013
Verlag: Springer US
Erschienen in: Journal of Intelligent Manufacturing / Ausgabe 6/2015
Print ISSN: 0956-5515
Elektronische ISSN: 1572-8145
DOI: https://doi.org/10.1007/s10845-013-0850-y

Premium Partner

Marktübersichten

Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.

Zur Marktübersicht

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 6/2015

Failure time prediction for mechanical device based on the degradation sequence

A graph-based pipe routing algorithm in aero-engine rotational space

Learning and reuse of engineering ramp-up strategies for modular assembly systems

A reinforcement learning based approach for a multiple-load carrier scheduling problem

A process prediction model based on Cuckoo algorithm for abrasive waterjet machining

A heuristic nonlinear operator for the aggregation of incomplete judgment matrices in group decision making

Premium Partner

Marktübersichten