- author = "Wen-Jun Yin and Min Liu and Cheng Wu",
- title = "Learning single-machine scheduling heuristics subject to machine breakdowns with genetic programming",
- booktitle = "Proceedings of the 2003 Congress on Evolutionary Computation CEC2003",
- editor = "Ruhul Sarker and Robert Reynolds and Hussein Abbass and Kay Chen Tan and Bob McKay and Daryl Essam and Tom Gedeon",
- pages = "1050--1055",
- year = "2003",
- publisher = "IEEE Press",
- volume = "2",
- address = "Canberra",
- publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA",
- month = "8-12 " # dec,
- organisation = "IEEE Neural Network Council (NNC), Engineers Australia (IEAust), Evolutionary Programming Society (EPS), Institution of Electrical Engineers (IEE)",
- keywords = "genetic algorithms, genetic programming, GP-evolved heuristics, bi-tree structured representation, idle time inserting programs, machine breakdowns, predictive scheduling heuristics, single-machine scheduling, heuristic programming, job shop scheduling, single machine scheduling, stochastic programming, tree searching",
- ISBN = "0-7803-7804-0",
-
DOI = "
doi:10.1109/CEC.2003.1299784",
- abstract = "Genetic Programming (GP) has been rarely applied to scheduling problems. In this paper the use of GP to learn single-machine predictive scheduling (PS) heuristics with stochastic breakdowns is investigated, where both tardiness and stability objectives in face of machine failures are considered. The proposed bi-tree structured representation scheme makes it possible to search sequencing and idle time inserting programs together. Empirical results in different uncertain environments show that GP can evolve high quality PS heuristics effectively. The roles of inserted idle time are then analysed with respect to various weighting objectives. Finally some guides are supplied for PS design based on GP-evolved heuristics.",
-
notes = "Also known as \cite{1299784}.
CEC 2003 - A joint meeting of the IEEE, the IEAust, the EPS, and the IEE.",
