JOBSHOP

JOBSHOP is a set of C programs for the job-shop scheduling problem. The codes are based on the paper ”A computational study of the job-shop scheduling problem” by David Applegate and William Cook (which appeared in ORSA Journal on Computing, Vol 3 No 2, 1991). The codes were written and tested on a variety of unix workstations in 1990. A set of test problems is included in the gzipped tarfile prob.tar.gz.


References in zbMATH (referenced in 94 articles , 1 standard article )

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  1. Müller, David; Müller, Marcus G.; Kress, Dominik; Pesch, Erwin: An algorithm selection approach for the flexible job shop scheduling problem: choosing constraint programming solvers through machine learning (2022)
  2. Strassl, Simon; Musliu, Nysret: Instance space analysis and algorithm selection for the job shop scheduling problem (2022)
  3. Kouider, Ahmed; Ait Haddadène, Hacène: A bi-objective branch-and-bound algorithm for the unit-time job shop scheduling: a mixed graph coloring approach (2021)
  4. Araujo, Janniele A. S.; Santos, Haroldo G.; Gendron, Bernard; Jena, Sanjay Dominik; Brito, Samuel S.; Souza, Danilo S.: Strong bounds for resource constrained project scheduling: preprocessing and cutting planes (2020)
  5. Da Col, Giacomo; Teppan, Erich: Google vs IBM: a constraint solving challenge on the job-shop scheduling problem (2019)
  6. Bürgy, Reinhard: A neighborhood for complex job shop scheduling problems with regular objectives (2017)
  7. Dabah, Adel; Bendjoudi, Ahcene; AitZai, Abdelhakim: An efficient tabu search neighborhood based on reconstruction strategy to solve the blocking job shop scheduling problem (2017)
  8. Ku, Wen-Yang; Beck, J. Christopher: Mixed integer programming models for job shop scheduling: A computational analysis (2016)
  9. Talbi, El-Ghazali: Combining metaheuristics with mathematical programming, constraint programming and machine learning (2016)
  10. Tan, Yi; Hildebrandt, Torsten; Scholz-Reiter, Bernd: Configuration and the advantages of the shifting bottleneck procedure for optimizing the job shop total weighted tardiness scheduling problem (2016)
  11. Grimes, Diarmuid; Hebrard, Emmanuel: Solving variants of the job shop scheduling problem through conflict-directed search (2015)
  12. Moin, Noor Hasnah; Chung Sin, Ong; Omar, Mohd: Hybrid genetic algorithm with multiparents crossover for job shop scheduling problems (2015)
  13. Peng, Bo; Lü, Zhipeng; Cheng, T. C. E.: A tabu search/path relinking algorithm to solve the job shop scheduling problem (2015)
  14. Fernando Gonçalves, José; Resende, Mauricio G. C.: An extended Akers graphical method with a biased random-key genetic algorithm for job-shop scheduling (2014)
  15. Spanos, Athanasios C.; Ponis, Stavros T.; Tatsiopoulos, Ilias P.; Christou, Ioannis T.; Rokou, Elena: A new hybrid parallel genetic algorithm for the job-shop scheduling problem (2014)
  16. Mencía, Carlos; Sierra, María R.; Varela, Ramiro: Depth-first heuristic search for the job shop scheduling problem (2013)
  17. Talbi, El-Ghazali: Combining metaheuristics with mathematical programming, constraint programming and machine learning (2013)
  18. González, Miguel Ángel; González-Rodríguez, Inés; Vela, Camino R.; Varela, Ramiro: An efficient hybrid evolutionary algorithm for scheduling with setup times and weighted tardiness minimization (2012) ioport
  19. González, Miguel A.; Vela, Camino R.; Varela, Ramiro: A competent memetic algorithm for complex scheduling (2012)
  20. Roli, Andrea; Benedettini, Stefano; Stützle, Thomas; Blum, Christian: Large neighbourhood search algorithms for the founder sequence reconstruction problem (2012)

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