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A novel problem dealing with design of reconfigurable automated machining lines is considered. Such lines are composed of workstations disposed sequentially. Each workstation needs the most suitable equipment. Each available piece of equipment is characterized by its cost, can perform a set of operations and requires skills of a given level for its maintenance. A multiobjective approach is proposed to assign tasks, choose and allocate pieces of equipment to workstations taking into account all the problem parameters and constraints. The techniques developed are based on a genetic algorithm of type NSGA-II. The NSGA-II suggested is also combined with a local search. These two genetic algorithms (with and without local search) are tested for several line examples and for two versions of the considered problem: bi-objective and four-objective cases. The results of numerical tests are reported. What is the most interesting is that the assessment of these algorithms is accomplished by using three measuring criteria: the direct measures of gaps, the measures proposed by Zitzler and Thiele in 1999 and the distances suggested by Riise in 2002.
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Tom
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4--17
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Bibliogr. 41 poz., rys., tab.
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autor
autor
autor
autor
autor
- Institut Charles Delaunay, UMR CNRS 6279 STMR, Laboratoire d'Optimisation des Systémes Industriels (LOSI), Université de Technologie de Troyes, 12, rue Marie Curie, BP2006 - 10010 Troyes cedex, France, phone: 0033 3 25 71 84 55, Hicham.chehade@utt.fr
Bibliografia
- [1] Askin R.G., Standridge C.R., Modeling and Analysis of Manufacturing Systems, John Wiley & Sons, 1993.
- [2] Hitomi K., Manufacturing System Engineering, Taylor & Francis, 1996.
- [3] Scholl A., Balancing and Sequencing of Assembly Lines, Physica-Verlag, 1999.
- [4] Dashchenko A.I. (Ed.), Manufacturing Technologies for Machines of the Future 21st Century Technologies, Springer, 2003.
- [5] Dolgui A., Proth J.-M., Les Systémes de Production Modernes, 2 volumes, Hermés Science, London, 2006.
- [6] Dolgui A., Proth J.-M., Supply Chain Engineering: Useful Methods and Techniques, Springer, 2010.
- [7] Baybars I., A survey of exact algorithms for the simple assembly line balancing, Management Science, 32, 909-932, 1986.
- [8] Talbot F.B., Patterson J.H., Gehrlein W.V., A comparative evaluation of heuristic line balancing techniques, Management Science, 32(4), 430-454, 1986.
- [9] Ghosh S., Gadnon R.J., A comprehensive literature review and analysis of the design, balancing and scheduling of assembly systems, International Journal of Production Research, 27, 637-670, 1989.
- [10] Erel E., Sarin S., A survey of the assembly line balancing procedures, Production Planning and Control, 9(5), 414-434, 1998.
- [11] Rekiek B., Dolgui A., Delchambre A., Bratcu A., State of art of assembly lines design optimization, Annual Reviews in Control, 26(2), 163-174, 2002.
- [12] Scholl A., Becker C., State-of-the-art exact and heuristic solution procedures for simple assembly line balancing, European Journal of Operational Research, 168, 666-693, 2006.
- [13] Guschinskaya O., Dolgui A., Equilibrage de lignes de production: état de l’art, Journal Européen des Systémes Automatisés, 44, 1081-1119, 2010.
- [14] Dolgui A., Finel B., Guschinsky N., Levin G., Vernadat F., An heuristic approach for transfer lines balancing, Journal of Intelligent Manufacturing, 16, 159-171, 2005.
- [15] Dolgui A., Finel B., Guschinsky N., Levin G., Vernadat F., MIP approach to balancing transfer lines with blocks of parallel operations, IIE Transactions, 38(10), 869-882, 2006.
- [16] Belmokhtar S., Dolgui A., Guschinsky N., Levin G., An integer programming model for logical layout design of modular machining lines, Computers and Industrial Engineering, 51(3), 502-518, 2006.
- [17] Dolgui A., Ihnatsenka I., Branch and bound algorithm for a transfer line design problem: Stations with sequentially activated multi-spindle heads, European Journal of Operational Research, 197, 1119-1132, 2009.
- [18] Graves S.C., Holmes R.C., Equipment selection and task assignment for multiproduct assembly system design, International Journal of Flexible Manufacturing Systems, 1, 31-50, 1988.
- [19] Szadkowski J., Critical path concept for multitool cutting processes optimization, Manufacturing, Modeling, Management and Control: A Proceedings Volume of the IFAC Symposium, Vienna, Austria, 393-398, 1997.
- [20] Bukchin J., Tzur M., Design of flexible assembly line to minimize equipment cost, IIE Transactions, 32, 585-598, 2000.
- [21] Ishibushi H., Yoshida T., Murata T., Balance between genetic search and local search in memetic algorithms for multi-objective permutation flowshop scheduling, IEEE Transactions on Evolutionary Computation, 7(2), 204-223, 2003.
- [22] Sysoev V., Dolgui A., A Pareto optimization approach for manufacturing system design, Proceedings of the International Conference on Industrial Engineering and Production Management (IEPM’99), book 1, 75-83, 1999.
- [23] Collette Y., Siarry P., Optimisation Multiobjectif, Edition Eyrolles, 2000.
- [24] Srinivas N., Deb K., Multi-objective function optimization using non-dominated sorting genetic algorithms, Evolutionary Computation Journal, 2(3), 221-248, 1994.
- [25] Fonseca C.M., Fleming P.J., An overview of evolutionary algorithms in multi-objective optimisation, Evolutionary Computation, 3(1), 1-16, 1995.
- [26] Sarker R., Liang Ko-H., Newton C., A new multi-objective evolutionary algorithm, European Journal of Operational Research, 140, 12-23, 2002.
- [27] Coello C., A comparative survey of evolutionary based multi-objective optimization techniques, Knowledge and Information Systems, 1, 269-308, 1999.
- [28] Horn J., Nafpliotis N., Multiobjective optimization using the Niched Pareto Genetic Algorithm, IlliGAL Report No.93005, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, 1993.
- [29] Zitzler E., Thiele L., Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach, IEEE Transactions on Evolutionary Computation, 3, 257-271, 1999.
- [30] Ponnambalam S.G., Aravindan P., Mogileeswar Nadiu G., A multi-objective genetic algorithm for solving assembly line balancing problem, International Journal of Advanced Manufacturing Technology, 16, 341-352, 2000.
- [31] Younes A., Ghenniwa H., Areibi S., An adaptive genetic algorithm for multi-objective flexible manufacturing systems, Proceedings of the Genetic and Evolutionary Computation Conference, 1241-1248, 2002.
- [32] Rekiek B., Pellichero F., De Lit P., Falkenauer E., Delchambre A., A resource planner for hybrid assembly lines, Proceedings of the 15th International Conference CAR & FOF’99, vol. 1, MW6-18-MW6-23, 1999.
- [33] Makdessian L., Yalaoui F., Dolgui A., Optimisation de lignes de production, Partie I: une approche monocritére, Journal of Decision Systems, 17, 313-336, 2008.
- [34] Makdessian L., Yalaoui F., Dolgui A., Optimisation de lignes de production, Partie II: une approche multicrit`ere, Journal of Decision Systems, 17, 337-368, 2008.
- [35] Riise A., Comparing genetic algorithms and tabu search for multiobjective optimization, Proceedings of the IFORS conference, Edinburgh, July 8-12, 2002.
- [36] Lacomme P., Prins C., Sevaux M., A genetic algorithm for a bi-objective capacitated arc routing problem, Computers & Operations Research, 33, 3473-3493, 2006.
- [37] Deb K., Agrawal S., Pratap A., Meyarivan T., A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II, Proceedings of Parallel Problem Solving from Nature VI, 849-858, 2000.
- [38] Deb K., Multi-objective genetic algorithms: Problem difficulties and construction of test problems, Evolutionary Computation Journal, 7(3), 205-230, 1999.
- [39] Deb K., Pratap A., Agarwal S., Meyarivan T., A fast and elitist multi-objective genetic algorithm: NSGAII, IEEE Transactions on Evolutionary Computation, 6(2), 182-197, 2002.
- [40] Chehade H., Amodeo L., Yalaoui F., A new hybrid multiobjective algorithm for assembly lines design, Proceedings of the World Congress in Computer Science, Computer Engineering and Applied Computing, Las Vegas, USA, July 13-16, 2009.
- [41] Dugardin F., Amodeo L., Yalaoui F., Méthodes multi-objectif pour l’ordonnancement de lignes réentrantes, Journal of Decision Systems, 18(2), 233-257, 2009.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAR0-0066-0001