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Heuristics for project scheduling with discounted cash flows optimisation

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The article presents the resource-constrained project scheduling problem with the maximisation of discounted cash flows from the contractor’s perspective: with cash outflows related to starting individual activities and with cash inflows for completing project stages (milestones). The authors propose algorithms for improving a forward active schedule by iterative one-unit right shifts of activities, taking into account different resource flow networks. To illustrate the algorithms and problem, a numerical example is presented. Finally, the algorithms are tested using standard test problems with additionally defined cash flows and contractual milestones.
Rocznik
Strony
613--622
Opis fizyczny
Bibliogr. 34 poz., rys., wykr.
Twórcy
autor
  • Department of Computer Science, Pope John Paul II State School of Higher Education, 95-97 Sidorska St., 21-500 Biała Podlaska, Poland
  • AGH University of Science and Technology, Department of Operations Research and Information Technology, 10 Gramatyka St., 30-067 Kraków, Poland
Bibliografia
  • [1] A.H. Russell, “Cash flows in networks”, Management Science 16, 357–373 (1970).
  • [2] M. Mika, G. Waligora, and J. Weglarz, “Simulated annealing and tabu search for multi-mode resource-constrained project scheduling with positive discounted cash flows and different payment models”, Eur. J. Operational Research 164 (3), 639–668 (2005).
  • [3] M. Vanhoucke, E. Demeulemeester, and W. Herroelen, “Maximizing the net present value of a project with linear time-dependent cash flows”, Int. J. Production Research 39 (14), 3159–3181 (2001).
  • [4] M. Klimek and P. Lebkowski, “An algorithm for maximising discounted cash flow problem of project settled with stages”, Innovations in Management and Production Engineering 1, 572–582 (2014), (in Polish).
  • [5] M. Klimek and P. Lebkowski, “Iterative right-shift algorithms for maximising the net present value of a project settled with stages”, Automation of Discrete Processes: Theory and Applications 2, 123–141 (2014), (in Polish).
  • [6] M. Klimek and P. Lebkowski, “A two-phase algorithm for a resource constrained project scheduling problem with discounted cash flows”, Decision Making in Manufacturing and Services 7 (1–2), 51–68 (2013).
  • [7] S. Hartmann and D. Briskorn, “A survey of variants and extensions of the resource-constrained project scheduling problem”, Eur. J. Operational Research 207 (1), 1–14 (2012).
  • [8] W. Herroelen, B.D. Reyck, and E. Demeulemeester, “Project network models with discounted cash flows: A guided tour through recent developments”, Eur. J. Operational Research 100, 97–121 (1997).
  • [9] N. Dayanand, R. Padman, “On modelling payments in projects”, J. Operational Research Society 48, 906–918 (1997).
  • [10] G. Ulusoy, F. Sivrikaya-Serifoglu, and S. Sahin, “Four payment models for the multi-mode resource constrained project scheduling problem with discounted cash flows”, Annals Operations Research 102, 237–261 (2001).
  • [11] N. Dayanand and R. Padman, “Project contracts and payment schedules: the client’s problem”, Management Science 47, 1654–1667 (2001).
  • [12] G. Ulusoy and S. Cebelli, “An equitable approach to the payment scheduling problem in project management”, Eur. J. Operational Research 127 (2), 262–278 (2000).
  • [13] Z. He and Y. Xu, “Multi-mode project payment scheduling problems with bonus penalty structure”, Eur. J. Operational Research 189 (3), 1191–1207 (2008).
  • [14] M. Klimek and P. Lebkowski, “Robustness of schedules for project scheduling problem with cash flow optimisation”, Bull. Pol. Ac.: Tech. 61 (4), 1005–1015 (2013).
  • [15] Z. He, N. Wang, T. Jia, and Y. Xu, “Simulated annealing and tabu search for multimode project payment scheduling”, Eur. J. Operational Research 198 (3), 688–696 (2009).
  • [16] Z. He, N. Wang, T. Jia, and Y. Xu, “Metaheuristics for multimode capital-constrained project payment scheduling”, Eur. J. Operational Research 223 (3), 605–613 (2012).
  • [17] R. Kolisch, “Serial and parallel resource-constrained project scheduling methods revisited: theory and computation”, Eur. J. Operational Research 90 (2), 320–333 (1996).
  • [18] R. Kolisch and A. Sprecher, “PSPLIB – a project scheduling library”, Eur. J. Operational Research 96, 205–216 (1997).
  • [19] M. Vanhoucke, “A scatter search procedure for maximizing the net present value of a resource-constrained project with fixed activity cash flows”, Working Paper 2006/417, 1–23 (2006).
  • [20] S.M. Baroum and J.H. Patterson, “The development of cash flow weight procedures for maximizing the net present value of a project”, J. Operations Management 14 (3), 209-27 (1996).
  • [21] G. Ulusoy and L. Özdamar, “A heuristic scheduling algorithm for improving the duration and net present value of a project”, Int. J. Operations and Production Management 15, 89–98 (1995).
  • [22] J.P. Pinder and A.S. Marucheck, “Using discounted cash flow heuristics to improve project net present value”, J. Operations Management 14, 229–240 (1996).
  • [23] J. Blazewicz, J. Lenstra, and A. Kan, “Scheduling subject to resource constraints – classification and complexity”, Discrete Applied Mathematics 5, 11–24 (1983).
  • [24] S. Hartmann and R. Kolisch, “Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem”, Eur. J. Operational Research 127, 394–407 (2000).
  • [25] R. Kolisch and S. Hartmann, “Experimental investigation of heuristics for resource-constrained project scheduling: an update”, Eur. J. Operational Research 174, 23–37 (2006).
  • [26] R. Kolisch and R. Padman, “An integrated survey of deterministic project scheduling”, OMEGA Int. J. Management Science 29, 249–272 (2001).
  • [27] S. Kirkpatrick, C.D. Gelatt, and M.P. Vecchi, “Optimization by simulated annealing”, Science 220, 671–680 (1983).
  • [28] K. Bouleimen and H. Lecocq, “A new efficient simulated annealing algorithm for the resource constrained project scheduling problem and its multiple version”, Eur. J. Operational Research 149, 268–281 (2003).
  • [29] R. Leus and W. Herroelen, “Stability and resource allocation in project planning”, IIE Trans. 36 (7), 667–682 (2004).
  • [30] F. Deblaere, E. Demeulemeester, W. Herroelen, and S. Van De Vonder, “Proactive resource allocation heuristics for robust project scheduling”, Research Report KBI 0608, CD-ROM (2006).
  • [31] N. Policella, “Scheduling with uncertainty – a proactive approach using partial order schedules”, PhD Thesis, University La Sapienza, Rome, 2005.
  • [32] M. Klimek and P. Lebkowski, “Resource allocation for robust project scheduling”, Bull. Pol. Ac.: Tech. 59 (1), 51–55 (2011).
  • [33] M. Klimek, “Predictive-reactive production scheduling with resource availability constraints”, PhD Thesis, AGH University of Science and Technology, Kraków, 2010, (in Polish).
  • [34] M. Aloulou and M. Portmann, “An efficient proactive reactive scheduling approach to hedge against shop floor disturbances”, 1st Multidisciplinary Conf. Scheduling: Theory and Applications 1, 337–362 (2003).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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