|
Gartland, K. (1999). Automated material handling system (AMHS) framework user requirements document: Version 1.0. International SEMATECH. Pillai, D. et al. (1999). Integration of 300 mm fab layouts and material handling auto-mation. In 1999 IEEE International Symposium on Semiconductor Manufac-turing Conference Proceedings (Cat No. 99CH36314) IEEE Press, pp. 23-26. Ruiz, R. et al. (2010). The hybrid flow shop scheduling problem. European journal of operational research, 205(1), 1-18. Gupta, J. N. (1988). Two-stage, hybrid flowshop scheduling problem. Journal of the Operational Research Society, 39(4), 359-364. Gourgand, M. et al. (2000). Meta-heuristics for the deterministic hybrid flow shop problem. Journal Europeen Des Systemes Automatises, 34(9), 1107-1136. Ying, K. C. et al. (2006). Multiprocessor task scheduling in multistage hybrid flow-shops: an ant colony system approach. International Journal of Produc-tion Research, 44(16), 3161-3177. Zandieh, M. et al. (2006). An immune algorithm approach to hybrid flow shops scheduling with sequence-dependent setup times. Applied Mathematics and Computation, 180(1), 111-127. Marichelvam, M. K. et al. (2017). Hybrid monkey search algorithm for flow shop scheduling problem under makespan and total flow time. Applied Soft Compu-ting, 55, 82-92. Shelokar, P. S. et al. (2007). Particle swarm and ant colony algorithms hybridized for improved continuous optimization. Applied mathematics and computa-tion, 188(1), 129-142. Kim, J. et al. (2016). Semiconductor FAB layout design analysis with 300-mm FAB data:“Is minimum distance-based layout design best for semiconductor FAB design?”. Computers & Industrial Engineering, 99, 330-346. Lee, S. et al. (2019). Iterative two-stage hybrid algorithm for the vehicle lifter location problem in semiconductor manufacturing. Journal of Manufacturing Systems, 51, 106-119. Wang, C. N., Hsu, H. P., Dang, D. C., & Nguyen, Q. T. (2019). The remaining time concept for dispatching on roller belt conveyor in 450-mm wafer fabrications. The International Journal of Advanced Manufacturing Technology, 1-15. Meller, R. D. (1997). The multi-bay manufacturing facility layout prob-lem. International Journal of Production Research, 35(5), 1229-1237. Castillo, I. et al. (2004). Integrating design and production planning considerations in multi-bay manufacturing facility layout. European Journal of Operational Re-search, 157(3), 671-687. Wang, H. et al. (2017). A NSGA-II based memetic algorithm for multiobjective par-allel flowshop scheduling problem. Computers & Industrial Engineering, 113, 185-194. Shahvari, O. et al. (2018). A comparison of two stage-based hybrid algorithms for a batch scheduling problem in hybrid flow shop with learning ef-fect. International Journal of Production Economics, 195, 227-248. Fu, Y. et al. (2019). Scheduling Dual-Objective Stochastic Hybrid Flow Shop With Deteriorating Jobs via Bi-Population Evolutionary Algorithm. IEEE Transac-tions on Systems, Man, and Cybernetics: Systems. Zhang, W. et al. (2019). Hybrid Multiobjective Evolutionary Algorithm based on Dif-ferential Evolution for Flow Shop Scheduling Problems. Computers & Indus-trial Engineering, 130, 661-670. Li, Z., et al. (2019). Bi-objective hybrid flow shop scheduling with common due date. Operational Research, 1-26. Pranzo, M. (2004). Batch scheduling in a two-machine flow shop with limited buffer and sequence independent setup times and removal times. European Journal of Operational Research, 153(3), 581-592. Wang, L. et al. (2006). An effective hybrid genetic algorithm for flow shop schedul-ing with limited buffers. Computers & Operations Research, 33(10), 2960-2971. Liu, B. et al. (2008). An effective hybrid PSO-based algorithm for flow shop sched-uling with limited buffers. Computers & Operations Research, 35(9), 2791-2806. Li, J. Q. et al. (2015). Solving the large-scale hybrid flow shop scheduling problem with limited buffers by a hybrid artificial bee colony algorithm. Information Sciences, 316, 487-502. Dugardin, F. et al. (2010). New multi-objective method to solve reentrant hybrid flow shop scheduling problem. European Journal of Operational Research, 203(1), 22-31. Ying, K. C. et al. (2014). Bi-objective reentrant hybrid flowshop scheduling: an iter-ated Pareto greedy algorithm. International Journal of Production Re-search, 52(19), 5735-5747. Shen, J. N. et al. (2016). A modified teaching–learning-based optimisation algorithm for bi-objective re-entrant hybrid flowshop scheduling. International Journal of Production Research, 54(12), 3622-3639. Cho, H. M. et al. (2017). A two-level method of production planning and scheduling for bi-objective reentrant hybrid flow shops. Computers & Industrial Engi-neering, 106, 174-181. Lee, B. et al. (2008). A due-date based production control policy using WIP balance for implementation in semiconductor fabrications. International Journal of Production Research, 46(20), 5515-5529. Cho, H. M. et al. (2012). Preemptive goal programming based heuristic methods for reentrant flow shop planning with bi-objective. Journal of the Society of Korea Industrial and Systems Engineering, 35. Deb, K. et al. (2000). A fast elitist non-dominated sorting genetic algorithm for mul-ti-objective optimization: NSGA-II. In International conference on parallel problem solving from nature. pp. 849-858. Springer, Berlin, Heidelberg. Cho, H. M. et al. (2011). Bi-objective scheduling for reentrant hybrid flow shop using Pareto genetic algorithm. Computers & Industrial Engineering, 61(3), 529-541. Mousavi, S. M. et al. (2018). An efficient bi-objective algorithm to solve re-entrant hybrid flow shop scheduling with learning effect and setup times. Operational Research, 18(1), 123-158. Zhang, X. Y. et al. (2018). A re-entrant hybrid flow shop scheduling problem with machine eligibility constraints. International Journal of Production Re-search, 56(16), 5293-5305. Agrawal, N. et al. (2006). Multi-objective optimization of the operation of an industri-al low-density polyethylene tubular reactor using genetic algorithm and its jumping gene adaptations. Industrial & engineering chemistry research, 45(9), 3182-3199. Bahri, N. et al. (2001). A comparison of unified vs. segregated automated material handling systems for 300 mm fabs. In 2001 IEEE International Symposium on Semiconductor Manufacturing. ISSM 2001. Conference Proceedings (Cat. No. 01CH37203). IEEE Press, pp. 3-6. Zhao, R. Q. et al. (2008). Monkey algorithm for global numerical optimiza-tion. Journal of Uncertain Systems, 2(3), 165-176. Nawaz, M. et al. (1983). A heuristic algorithm for the m-machine, n-job flow-shop se-quencing problem. Omega, 11(1), 91-95. Tseng, L. Y. et al. (2010). A hybrid genetic algorithm for no-wait flowshop scheduling problem. International journal of production economics, 128(1), 144-152. Ding, J. Y. et al. (2015). An improved iterated greedy algorithm with a Tabu-based reconstruction strategy for the no-wait flowshop scheduling problem. Applied Soft Computing, 30, 604-613. Bean, J. C. (1994). Genetic algorithms and random keys for sequencing and optimiza-tion. ORSA journal on computing, 6(2), 154-160. Tasgetiren, M. F. et al. (2007). A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem. European journal of operational research, 177(3), 1930-1947. Rajkumar, R. et al. (2009). An improved genetic algorithm for the flowshop schedul-ing problem. International Journal of Production Research, 47(1), 233-249.
|