Abstract
In recent years, in the field of project scheduling the concept of partially renewable resources has been introduced. Theoretically, it is a generalization of both renewable and non-renewable resources. From an applied point of view, partially renewable resources allow us to model a large variety of situations that do not fit into classical models, but can be found in real problems in timetabling and labor scheduling. In this chapter we define this type of resource, describe an integer linear formulation and present some examples of conditions appearing in real problems which can be modeled using partially renewable resources. Then we introduce some preprocessing procedures to identify infeasible instances and to reduce the size of the feasible ones. Some exact, heuristic, and metaheuristic algorithms are also described and tested.
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References
Alvarez-Valdes R, Crespo E, Tamarit JM, Villa F (2006) GRASP and path relinking for project scheduling under partially renewable resources. Eur J Oper Res 189:1153–1170
Alvarez-Valdes R, Crespo E, Tamarit JM, Villa F (2008) A scatter search algorithm for project scheduling under partially renewable resources. J Heuristics 12:95–113
Böttcher J, Drexl A, Kolisch R, Salewski F (1999) Project scheduling under partially renewable resource constraints. Manage Sci 45:544–559
Chaudhuri S, Walker RA, Mitchell JE (1994) Analyzing and exploiting the structure of the constraints in the ILP approach to the scheduling problem. IEEE T VLSI Syst 2:456–471
Christofides N, Alvarez-Valdes R, Tamarit JM (1987) Project scheduling with resource constraints: a branch and bound approach. Eur J Oper Res 29:262–273
de Boer(1998) Resource-constrained multi-project management: a hierarchical decision support system. Ph.D. dissertation, University of Twente, Twente, The Netherlands
Kolisch R, Sprecher A, Drexl A (1995) Characterization and generation of a general class of resource-constrained project scheduling problems. Manage Sci 41:1693–1703
Laguna M, Marti R (2004) Scatter search. Kluwer, Boston
Mellentien C, Schwindt C, Trautmann N (2004) Scheduling the factory pick-up of new cars. OR Spectr 26:579–601
Neumann K, Schwindt C, Trautmann N (2002) Advanced production scheduling for batch plants in process industries. OR Spectr 24:251–279
Neumann K, Schwindt C, Trautmann N (2005) Scheduling of continuous and discontinuous material flows with intermediate storage restrictions. Eur J Oper Res 165:495–509
Resende, MGC, Ribeiro CC (2003) Greedy randomized adaptive search procedures. In: Glover F, Kochenbeger G (eds) Handbook of metaheuristics. Kluwer, Boston, pp 219–249
Schirmer A (2000) Project scheduling with scarce resources. Dr. Kovac, Hamburg
Schwindt C, Trautmann N (2003) Scheduling the production of rolling ingots: industrial context, model and solution method. Int Trans Oper Res 10:547–563
Shewchuk JP, Chang TC (1995) Resource-constrained job scheduling with recyclable resources. Eur J Oper Res 81:364–375
Talbot FB, Patterson JH (1978) An efficient integer programming algorithm with network cuts fo solving resource-constrained project scheduling problems. Manage Sci 24:1163–1174
Acknowledgements
This work has been partially supported by the Spanish Ministry of Education and Science DPI2011-24977.
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Alvarez-Valdes, R., Tamarit, J.M., Villa, F. (2015). Partially Renewable Resources. In: Schwindt, C., Zimmermann, J. (eds) Handbook on Project Management and Scheduling Vol.1. International Handbooks on Information Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-05443-8_11
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DOI: https://doi.org/10.1007/978-3-319-05443-8_11
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