Enhancing rule-based scheduling in wafer fabrication facilities by evolutionary algorithms: Review and opportunity
暂无分享,去创建一个
[1] Deming Lei,et al. Multi-objective production scheduling: a survey , 2009 .
[2] Zhibin Jiang,et al. A multi-objective dynamic scheduling approach using multiple attribute decision making in semiconductor manufacturing , 2011 .
[3] Egon Balas,et al. The Shifting Bottleneck Procedure for Job Shop Scheduling , 1988 .
[4] Sung-Bae Cho,et al. An efficient genetic algorithm with less fitness evaluation by clustering , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).
[5] Mitsuo Gen,et al. Evolutionary techniques for optimization problems in integrated manufacturing system: State-of-the-art-survey , 2009, Comput. Ind. Eng..
[6] John W. Fowler,et al. A combined dispatching criteria approach to scheduling semiconductor manufacturing systems , 2001 .
[7] Bernd Scholz-Reiter,et al. Generating dispatching rules for semiconductor manufacturing to minimize weighted tardiness , 2010, Proceedings of the 2010 Winter Simulation Conference.
[8] Enrique Alba,et al. New Technologies in Parallelism , 2005 .
[9] Sunil Vadera,et al. AI and OR in management of operations: history and trends , 2007, J. Oper. Res. Soc..
[10] Michael E. Kuhl,et al. A simulation study of new multi-objective composite dispatching rules, CONWIP, and push lot release in semiconductor fabrication , 2008 .
[11] Hark Hwang,et al. Simplification methods for accelerating simulation-based real-time scheduling in a semiconductor wafer fabrication facility , 2003 .
[12] Kevin Tucker,et al. Response surface approximation of pareto optimal front in multi-objective optimization , 2004 .
[13] Yeong-Dae Kim,et al. Production scheduling in a semiconductor wafer fabrication facility producing multiple product types with distinct due dates , 2001, IEEE Trans. Robotics Autom..
[14] Khaled Rasheed,et al. A Survey of Fitness Approximation Methods Applied in Evolutionary Algorithms , 2010 .
[15] C. A. Coello Coello,et al. Evolutionary multi-objective optimization: a historical view of the field , 2006, IEEE Computational Intelligence Magazine.
[16] Barbara Chapman,et al. Using OpenMP - portable shared memory parallel programming , 2007, Scientific and engineering computation.
[17] Graham Kendall,et al. Hyper-Heuristics: An Emerging Direction in Modern Search Technology , 2003, Handbook of Metaheuristics.
[18] Min-Jea Tahk,et al. Acceleration of the convergence speed of evolutionary algorithms using multi-layer neural networks , 2003 .
[19] Nhu Binh Ho,et al. Evolving dispatching rules using genetic programming for solving multi-objective flexible job-shop problems , 2008, Comput. Ind. Eng..
[20] David B. Pratt,et al. The modified critical ratio: towards sequencing with a continuous decision domain , 2005 .
[21] Li-Chen Fu,et al. Parameter tuning of production scheduling rules by an ant system-embedded genetic algorithm , 2004, IEEE Conference on Robotics, Automation and Mechatronics, 2004..
[22] Haldun Aytug,et al. Use of genetic algorithms to solve production and operations management problems: A review , 2003 .
[23] Appa Iyer Sivakumar,et al. Job shop scheduling techniques in semiconductor manufacturing , 2006 .
[24] Serge Domenech,et al. Multiobjective scheduling for semiconductor manufacturing plants , 2010, Comput. Chem. Eng..
[25] Erwin Pesch,et al. Evolution based learning in a job shop scheduling environment , 1995, Comput. Oper. Res..
[26] Sanja Petrovic,et al. A new dispatching rule based genetic algorithm for the multi-objective job shop problem , 2010, J. Heuristics.
[27] John W. Fowler,et al. A multi-criteria approach for scheduling semiconductor wafer fabrication facilities , 2008, J. Sched..
[28] Z. B. Jiang,et al. Multiple-objective scheduling and real-time dispatching for the semiconductor manufacturing system , 2009, Comput. Oper. Res..
[29] Qingfu Zhang,et al. Multiobjective evolutionary algorithms: A survey of the state of the art , 2011, Swarm Evol. Comput..
[30] Reha Uzsoy,et al. Rapid Modeling and Discovery of Priority Dispatching Rules: An Autonomous Learning Approach , 2006, J. Sched..
[31] James C. Chen,et al. A study of the flexible job shop scheduling problem with parallel machines and reentrant process , 2008 .
[32] Pedro A. Castillo,et al. GPU Computation in Bioinspired Algorithms: A Review , 2011, IWANN.
[33] Michael Pinedo,et al. Scheduling: Theory, Algorithms, and Systems , 1994 .
[34] John W. Fowler,et al. A survey of problems, solution techniques, and future challenges in scheduling semiconductor manufacturing operations , 2011, J. Sched..
[35] Peter Ross,et al. Evolutionary Scheduling: A Review , 2005, Genetic Programming and Evolvable Machines.
[36] John W. Fowler,et al. Heuristic scheduling of jobs on parallel batch machines with incompatible job families and unequal ready times , 2005, Comput. Oper. Res..
[37] Barbara Chapman,et al. Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation) , 2007 .
[38] John W. Fowler,et al. A genetic algorithm approach to manage ion implantation processes in wafer fabrication , 2000, Int. J. Manuf. Technol. Manag..
[39] Muh-Cherng Wu,et al. Dispatching for make-to-order wafer fabs with machine-dedication and mask set-up characteristics , 2008 .
[40] Chung Yee Lee,et al. GLOBAL JOB SHOP SCHEDULING WITH A GENETIC ALGORITHM , 1995 .
[41] Tsung-Che Chiang. Model simplification for accelerating simulation-based evaluation of dispatching rules in wafer fabrication facilities , 2010, 2010 11th International Conference on Control Automation Robotics & Vision.
[42] Scott J. Mason,et al. Parallel machine scheduling subject to auxiliary resource constraints , 2007 .
[43] C. Hicks,et al. An ordinal optimization based evolution strategy to schedule complex make-to-order products , 2006 .
[44] Li-Chen Fu,et al. Petri-net and GA-based approach to modeling, scheduling, and performance evaluation for wafer fabrication , 2000, IEEE Trans. Robotics Autom..
[45] Qingfu Zhang,et al. Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model , 2010, IEEE Transactions on Evolutionary Computation.
[46] Wan Chul Yoon,et al. A spatial rule adaptation procedure for reliable production control in a wafer fabrication system , 1998 .
[47] Taho Yang,et al. A genetic algorithms simulation approach for the multi-attribute combinatorial dispatching decision problem , 2007, Eur. J. Oper. Res..
[48] Subhash C. Sarin,et al. A survey of dispatching rules for operational control in wafer fabrication , 2011 .
[49] Cathal Heavey,et al. A comparison of genetic programming and artificial neural networks in metamodeling of discrete-event simulation models , 2012, Comput. Oper. Res..
[50] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..
[51] Mingyuan Chen,et al. A parallel genetic algorithm for a flexible job-shop scheduling problem with sequence dependent setups , 2010 .
[52] R. Haftka,et al. Ensemble of surrogates , 2007 .
[53] Pravin K. Johri,et al. Practical issues in scheduling and dispatching in semiconductor wafer fabrication , 1993 .
[54] S. S. Chaudhry *,et al. Application of genetic algorithms in production and operations management: a review , 2005 .
[55] Giovanni Miragliotta,et al. Decentralised, multi-objective driven scheduling for reentrant shops: A conceptual development and a test case , 2005, Eur. J. Oper. Res..
[56] Barry Wilkinson,et al. Parallel programming , 1998 .
[57] Yuehwern Yih,et al. Selection of dispatching rules on multiple dispatching decision points in real-time scheduling of a semiconductor wafer fabrication system , 2003 .
[58] Liang Shi,et al. Multiobjective GA optimization using reduced models , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[59] Reha Uzsoy,et al. A review of production planning and scheduling models in the semiconductor industry , 1994 .
[60] M. Mathirajan,et al. A literature review, classification and simple meta-analysis on scheduling of batch processors in semiconductor , 2006 .
[61] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[62] Vidroha Debroy,et al. Genetic Programming , 1998, Lecture Notes in Computer Science.
[63] Chen-Fu Chien,et al. A novel timetabling algorithm for a furnace process for semiconductor fabrication with constrained waiting and frequency-based setups , 2007, OR Spectr..
[64] Enrique Alba,et al. Parallel Genetic Algorithms , 2020, Studies in Computational Intelligence.
[65] Enrique Alba,et al. Parallelism and evolutionary algorithms , 2002, IEEE Trans. Evol. Comput..
[66] Mehmet Mutlu Yenisey,et al. Scheduling Practice and Recent Developments in Flow Shop and Job Shop Scheduling , 2009 .
[67] Rajesh Piplani,et al. Simplification strategies for simulation models of semiconductor facilities , 2004 .
[68] Li-Chen Fu,et al. A memetic algorithm for minimizing total weighted tardiness on parallel batch machines with incompatible job families and dynamic job arrival , 2010, Comput. Oper. Res..
[69] John W. Fowler,et al. Genetic algorithm-based subproblem solution procedures for a modified shifting bottleneck heuristic for complex job shops , 2007, Eur. J. Oper. Res..
[70] D. Y. Sha,et al. A simulated annealing algorithm for integration of shop floor control strategies in semiconductor wafer fabrication , 2003 .
[71] Yan Chen,et al. Scheduling jobs on parallel machines with setup times and ready times , 2008, Comput. Ind. Eng..
[72] S.J. Mason,et al. Metaheuristic scheduling of 300-mm lots containing multiple orders , 2005, IEEE Transactions on Semiconductor Manufacturing.
[73] R. Uzsoy,et al. A problem reduction approach for scheduling semiconductor wafer fabrication facilities , 2006, IEEE Transactions on Semiconductor Manufacturing.
[74] Samir Barman,et al. The impact of priority rule combinations on lateness and tardiness , 1998 .
[75] Tong Heng Lee,et al. Multiobjective Evolutionary Algorithms and Applications , 2005, Advanced Information and Knowledge Processing.
[76] Christopher D. Geiger,et al. Learning effective dispatching rules for batch processor scheduling , 2008 .
[77] Panos M. Pardalos,et al. Parallel hybrid heuristics for the permutation flow shop problem , 2012, Annals of Operations Research.
[78] Zhibin Jiang,et al. An optimised dynamic bottleneck dispatching policy for semiconductor wafer fabrication , 2009 .
[79] Li-Chen Fu,et al. A new paradigm for rule-based scheduling in the wafer probe centre , 2008 .
[80] Haym Hirsh,et al. Informed operators: Speeding up genetic-algorithm-based design optimization using reduced models , 2000, GECCO.
[81] Mitsuo Gen,et al. A tutorial survey of job-shop scheduling problems using genetic algorithms—I: representation , 1996 .
[82] Dirk Reichelt,et al. Multiobjective Scheduling of Jobs with Incompatible Families on Parallel Batch Machines , 2006, EvoCOP.
[83] Joshua D. Knowles,et al. ParEGO: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems , 2006, IEEE Transactions on Evolutionary Computation.
[84] Chen-Fu Chien,et al. Using genetic algorithms (GA) and a coloured timed Petri net (CTPN) for modelling the optimization-based schedule generator of a generic production scheduling system , 2007 .
[85] Zhibin Jiang,et al. Simulation-based optimization of dispatching rules for semiconductor wafer fabrication system scheduling by the response surface methodology , 2009 .
[86] Cheng Wu,et al. Genetic algorithm using sequence rule chain for multi-objective optimization in re-entrant micro-electronic production line , 2004 .
[87] A.I. Sivakumar,et al. Online multiobjective Pareto optimal dynamic scheduling of semiconductor back-end using conjunctive simulated scheduling , 2006, IEEE Transactions on Electronics Packaging Manufacturing.
[88] Muh-Cherng Wu,et al. Scheduling semiconductor in-line steppers in new product/process introduction scenarios , 2010 .
[89] J. C. Chen *,et al. Dynamic state-dependent dispatching for wafer fabrication , 2004 .
[90] Lars Mönch,et al. Genetic algorithms to solve a single machine multiple orders per job scheduling problem , 2010, Proceedings of the 2010 Winter Simulation Conference.
[91] D. Goldberg,et al. Don't evaluate, inherit , 2001 .
[92] Mehrdad Tamiz,et al. Multi-objective meta-heuristics: An overview of the current state-of-the-art , 2002, Eur. J. Oper. Res..
[93] Lars Mönch,et al. Machine learning techniques for scheduling jobs with incompatible families and unequal ready times on parallel batch machines , 2006, Eng. Appl. Artif. Intell..
[94] Ali M. S. Zalzala,et al. Recent developments in evolutionary computation for manufacturing optimization: problems, solutions, and comparisons , 2000, IEEE Trans. Evol. Comput..
[95] Enrique Alba,et al. Parallel Metaheuristics: A New Class of Algorithms , 2005 .
[96] Lin Danping,et al. A review of the research methodology for the re-entrant scheduling problem , 2011 .
[97] Robert E. Smith,et al. Fitness inheritance in genetic algorithms , 1995, SAC '95.
[98] P. N. Suganthan,et al. Differential Evolution: A Survey of the State-of-the-Art , 2011, IEEE Transactions on Evolutionary Computation.
[99] David Stockton,et al. Control point policy optimization using genetic algorithms , 2008 .
[100] Wojciech Bozejko,et al. Parallel hybrid metaheuristics for the flexible job shop problem , 2010, Comput. Ind. Eng..
[101] Rubén Ruiz,et al. Operational planning and control of semiconductor wafer production , 2006 .
[102] Li-Chen Fu,et al. Modeling, scheduling, and performance evaluation for wafer fabrication: a queueing colored Petri-net and GA-based approach , 2006, IEEE Trans Autom. Sci. Eng..
[103] Carlos A. Coello Coello,et al. A Review of Techniques for Handling Expensive Functions in Evolutionary Multi-Objective Optimization , 2010 .