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Project oriented production optimization

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper the resource - constrained scheduling problem is discussed. The objective function is minimization of makespan under constrained resources and due time. The metaheuristic based on Ant Colony Optimization (ACO) is proposed for multi-project scheduling. The elaborated method, algorithm and example illustrating ACO application for the multi-project scheduling problem is presented.
Rocznik
Strony
80--90
Opis fizyczny
Bibliogr. 37 poz., tab., rys.
Twórcy
autor
  • Silesian University Of Technology, Faculty of Mechanical Engineering, Institute Of Engineering Processes Automation And Integrated Manufacturing Systems, Gliwice, Poland
  • Silesian University Of Technology, Faculty of Mechanical Engineering, Institute Of Engineering Processes Automation And Integrated Manufacturing Systems, Gliwice, Poland
Bibliografia
  • [1] SKOŁUD B., 2007, Operational management. Production in small and medium-sized enterprises, Wydawnictwo Politechniki Śląskiej, 238.
  • [2] LEACH L.P.J., 2000, Critical Chain Project Management, Artech House, Norwood.
  • [3] BRILMAN J., 2002, Modern management concepts and methods, PWE, Warszawa.
  • [4] LEACH L.P., 2000, Critical Chain Project Management, Artach Mouse, Boston.
  • [5] WALL M.B., 1996, A Genetic Algorithm for Resource – Constrained Scheduling, Doctoral Dissertation for Mechanical Engineering at the Massachusetts Institute of Technology.
  • [6] MINGOZZI A., MANIEZZO V., RICCIARDELLI S., BIANCO L., 1995, An Exact Algorithm for the Resource Constrained Project Scheduling Problem Based on a New Mathematical Formulation, in: www.csr.unibo.it/~maniezzo/pspaper.ps
  • [7] KOLISCH R., HARTMANN S., 1999, Heuristic algorithms for solving the resource-constrained project scheduling problem: Classification and computational analysis, In: Weglarz, J. (Ed.), Handbook on Recent Advances in Project Scheduling. Kluwer, Dordrecht, 147-178.
  • [8] LEE J. K., KIM Y. D., 1996, Search heuristics for resource-constrained project scheduling, Journal of the Operational Research Society, 47, 678–689.
  • [9] J. ALCARAZ, C. MAROTO 2001, A robust genetic algorithm for resource allocation in project scheduling, Annals of Operations Research, Vol. 102, pp.83–109.
  • [10] BOCTOR F. F.,1996, An adaptation of the simulated annealing algorithm for solving resource-constrained project scheduling problems, International Journal of Production Research, 34, 2335–2351.
  • [11] BOULEIMEN K., LECOCQ H., 2003, A new efficient simulated annealing algorithm for the resourceconstrained project scheduling problem and its multiple mode version, European Journal of Operational Research, 149, 268-281.
  • [12] PINSON E., PRINS C., RULLIER F., 1994, Using tabu search for solving the resource-constrained project scheduling problem, Proceedings of the 4th International Workshop on Project Management and Scheduling, Leuven, Belgium, 102–106.
  • [13] MERKLE D., MIDDENDORF M., SCHMECK H., 2002, Ant colony optimization for resource-constrained project scheduling, IEEE Transactions on Evolutionary Computation, 6, 333–346.
  • [14] PRITSKER A., ALLAN B., WATTERS L. J., WOLFE P. M., 1969, Multiproject scheduling with limited resources: A zero-one programming approach, Management Science, 16, 93– 108.
  • [15] TSUBAKITANI S., DECKRO R. F., 1990, A Heuristic For Multi-Project Scheduling With Limited Resources In The Housing Industry, European Journal of Operational Research, 49, 80–91.
  • [16] LAWRENCE S. R., MORTON T. E., 1993, Resource-constrained multi-project scheduling with tardy costs: Comparing myopic bottleneck and resource pricing heuristics, European Journal of Operational Research, 64, 168-187.
  • [17] WILEY V. D., DECKRO R. F., JACKSON J. A., 1998, Optimization analysis for design and planning of multiproject programs, European Journal of Operational Research, 107, 492–506.
  • [18] LOVA A., MAROTO C., TORMOS P., 2000, A multicriteria heuristic method to improve resource allocation in multiproject scheduling, European Journal of Operational Research, 127, 408– 424.
  • [19] BLAZEWICZ J., LENSTRA J. K., RINNOOY KAN A.H.G., 1983, Scheduling Projects to Resource Constraints: Classification and Complexity, Discrete Applied Mathematics, 5, 11-24.
  • [20] BLUM CH., 2005, Ant colony optimization: Introduction and recent trends, Physics of live reviews, 2005.
  • [21] DORIGO M.,. MANIEZZO V, COLORNI A., 1996, The Ant System: Optimization by a Colony of Cooperating Agents, IEEE Systems, Man and Cybernetics, Italy.
  • [22] ABDALLAH H., EMARA H.M., DORRAH H.T., BAHGAT A., 2009, Using Ant Colony optimization algorithm for solving project management problem, IJ of Expert Systems with Application, 36, 10004-10015.
  • [23] M. DORIGO M., MANIEZZO V., COLORNI A. 1991, Positive Feedback as a Search Strategy, Technical Report, 91-116, Politechnico di Milano, Milano.
  • [24] DONG G., GUO W., TICKLE K., 2012, Solving the traveling salesman problem using cooperative genetic ant systems, Expert Systems with Applications, Apr 2012, 39/5, 5006-5011.
  • [25] GAMBARDELLA L.M., TAILLARD E.D., DORIGO M., 1997, Ant Colonies for the QAP, Technical Report, 4-97, IDSIA, Lugano, Switzerland.
  • [26] PHEN C.S., KUAN Y.W., KOMARUDIN, 2009, Assessment Guidelines for Ant Colony Algorithms when Solving Quadratic Assignment Problems, AIP Conference Proceedings, 8/13/2009, 1148/1, 865-867.
  • [27] BULLNHEIMER B., HARTL R.F., STRAUSS C., 1999, Applying the Ant System to the Vehicle Routing Problem, Metaheuristics, Advances and Trends in Local Search Paradigms for Optimization, Eds. I.H. Osman, S. Voß, S. Martello, C. Roucairol, Kluwer Academic Publishers, Boston, 109-120.
  • [28] ÇATAY B., 2010, A new saving-based ant algorithm for the Vehicle Routing Problem with Simultaneous Pickup and Delivery, Expert Systems with Applications, 37/10, 6809-6817.
  • [29] CORRY P., KOZAN E., 2004, Ant Colony Optimization for the Machine Layout Problem, computational Optimization And Applications, 28/3, 287-310.
  • [30] SEO M., KIM D., 2010, Ant colony optimisation with parameterised search space for the job shop scheduling problem. International Journal of Production Research, 48/4, 1143-1154.
  • [31] MIRABI M., 2011, Ant colony optimization technique for the sequence-dependent flowshop scheduling problem,International Journal of Advanced Manufacturing Technology, 55/1-4, 317-326.
  • [32] SOLIMANPUR M., VRAT P., SHANKAR R., 2005, An ant algorithm for the single row layout problem in flexible manufacturing systems, Computers & Operations Research, 32/3, 583-598.
  • [33] ZHANG H., 2012, Ant Colony Optimization for Multimode Resource-Constrained Project Scheduling, Journal of Management in Engineering, 28/2, 150-159.
  • [34] CHRISTODOULOU S., 2010, Scheduling Resource-Constrained Projects with Ant Colony Optimization Artificial Agents, Journal of Computing in Civil Engineering, 24/1, 45-55.
  • [35] CHEN W., SHI Y., TENG H., LAN X., HU L., 2010, An efficient hybrid algorithm for resource-constrained project scheduling, Information Sciences, 180/6, 1031-1039.
  • [36] BORYCZKA U., 2006, Algorithms of the ant colony optimization, Publishing house of University of Silesia, Katowice.
  • [37] DORIGO M., STUTZLE T., 2004, Ant Colony, Optimization, Massachusetts Institute of Technology.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a6109b5a-b229-4c7e-a3a7-9f8477d413ff
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