PSPLIB-ENERGY: a extension of PSPLIB library to assess the energy optimization in the RCPSP

Authors

  • Daniel Morillo Torres
  • Federico Barber
  • Miguel A. Salido

DOI:

https://doi.org/10.4114/intartif.vol17iss54pp48-61

Abstract

Scheduling problems is one of the core areas in the planning and development of any project, with a wide applicability to real-world situations. Due to the high complexity of these problems, the solving process is often based on metaheuristics techniques, so that the evaluation of these methods is empirical. Therefore benchmarks, which provide a set of test cases to assess the behavior of algorithms, are generated. This paper extends the PSPLIB library. This extension incorporates to each instance of RCPSP (Resource Constrained Project Scheduling Problem), a realistic mathematical model of energy consumption. This proposal provides an alternative to the current trend in the eld of optimization and manufacturing that requires the inclusion of components and methods that reduce the environmental impact in the process of decision making. Finally a new optimality criterion is proposed to compare dierent search techniques. The PSPLIB-ENERGY is available at http://gps. webs.upv.es/psplib-energy/.

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Published

2014-12-18

How to Cite

Morillo Torres, D., Barber, F., & Salido, M. A. (2014). PSPLIB-ENERGY: a extension of PSPLIB library to assess the energy optimization in the RCPSP. Inteligencia Artificial, 17(54), 48-61. https://doi.org/10.4114/intartif.vol17iss54pp48-61