AGV Automatic guided vehicle
AI Artificial intelligence
CLSD Closest distance
CYC Cyclic
EDD Earliest due date
FCFS First come first served
FIFO First in first out
FIGURE 5.11 Conclusion modification for rule 1.
FIGURE 5.12 Conclusion modification for rule 2.
1.0 0 9.0 K 6.0 10 0 100% L 90% 1 0 Due-date tightness µ 1.0 0 9.0 K 1 6.0 µ 10% 0 100% L 1 90% µ 1 0 Due-date tightness 1 S2 A2 j S S j n j j n j =
( )
1 ×( )
IOT +( )
2 ×(
SLRO)
, ,LULIB Lowest utilization of local input buffer MAW Modified additive weighting
MCD Multi-criterion decision making
NINQ Number of parts in queue
PM Performance measure
POR Preferred order
RAN Random
SAW Simple additive weighting
SDS Shortest distance to station SIO Shortest imminent operation time SIOx or SIx Truncated SIO
SLACK Shortest remaining slack time
SLACK/RO Slack per number of remaining operations SLRO Ratio of slack to remaining operation time
SNQ Shortest number in queue
SPT Shortest processing time
SRPT Shortest remaining processing time STPT Shortest total processing time
TWK Total work
WINQ Work in queue
WIP Work in process
References
Arbel, A. 1989, Approximate articulation of preference and priority derivation, European Journal of
Operational Research, vol. 43, pp. 317-326.
Arbel, A. and Vargas, G. L. 1993, Preference simulation and preference programming: robustness issues in priority derivation, European Journal of Operational Research, vol. 69, pp. 200-209.
Baid, N. K. and Nagarur, N. N. 1994, An integrated decision support system for FMS: using intelligent simulation, International Journal of Production Research, vol. 32, no. 4, pp. 951-965.
Baker, K. R. 1984, Sequencing rules and due-date assignments in a job shop, Management Science, vol. 30, no. 9, pp. 1093-1104.
Ballakur, A. and Steudel, H. J. 1984, Integration of job shop control systems: a state-of-the-art review,
Journal of Manufacturing Systems, vol. 3, no. 1, pp. 71-79.
Bellman, R. E. and Zadeh, L. A. 1970, Decision making in a fuzzy environment, Management Science, vol. 17, pp. 141-164.
Blackstone, J. H., Philips, D. T. and Hogg, G. L. 1982, A state of the art survey of dispatching rules for job shop operations, International Journal of Production Research, vol. 20, no. 1, pp. 27-45. Chen, I. J. and Chung, C. H. 1991, Effects of loading and routing decisions on performance flexible
manufacturing systems, International Journal of Production Research, vol. 29, pp. 2209-2225. Chryssolouris, G., Dicke, K. and Moshine, L. 1994, An approach to real-time flexible scheduling, Inter-
national Journal of Flexible Manufacturing Systems, vol. 6, pp. 235-253.
Darvishi, A. R. and Gill, K. F. 1990, Expert system design for fixture design, International Journal of
Production Research, vol 28, no. 10, pp. 1901-1920.
Dweiri, F. and Meier, F. A. 1996, Application of fuzzy decision-making in facilities layout planning,
systems, International Journal of Computer Integrated Manufacturing, vol. 2, no. 6, pp. 356-377. Hang, C. L. and Yon, K. 1981, Multiple Attribute Decision Making, Springer-Verlag, New York.
Hutchison, J. and Khumavala, B. 1990, Scheduling random flexible manufacturing systems with dynamic environments, Journal of Operations Management, vol. 9, no. 3, pp. 335-351.
Karwowski, W. and Evans, G. W. 1986, Fuzzy concepts in production management research: a review,
International Journal of Production Research, vol. 24, no. 1, pp. 129-147.
Kazerooni, A., Chan, F. T. S., Abhary, K. and Ip, R. W. L. 1996, Simulation of scheduling rules in a flexible manufacturing system using fuzzy logic, IEA-AIE96 Ninth International Conference on Industrial
and Engineering Application of Artificial Intelligence and Expert System, Japan, pp. 491-500.
Mamdani, E. H. 1974, Application of fuzzy algorithms for control of simple dynamic plant, Proceeding
of IEE, vol. 121, no. 12, pp. 1585-1588.
McCartney, J. C. and Hinds, B. K. 1981, Interactive scheduling procedures for FMS, Proceedings of 22nd
International Machine Tool Design and Research Conference, Manchester, U.K., pp. 47-54.
Mellichamp, J. M., Kwon, O. J. and Wahab, A. F. A. 1990, FMS designer: an expert system for flexible manufacturing system design, International Journal of Production Research, vol. 28, no. 11, pp. 2013-2024.
Montazeri, M. and Van Wassenhove, L. N. 1990, Analysis of scheduling rules for an FMS, International
Journal of Production Research, vol. 28, no. 4, pp. 785-802.
Naruo, N., Lehto, M. and Salvendy, G. 1990, Development of a knowledge-based decision support system for diagnosing malfunctions of advanced production equipment, International Journal of Produc-
tion Research, vol. 28, no. 12, pp. 2259-2276.
O’Keefe, R. M. and Rao, R. 1992, Part input into a flexible input flow system: an evaluation of look- ahead simulation and a fuzzy rule base, International Journal of Flexible Manufacturing Systems, vol. 4, pp. 113-127.
Petrovic, D. and Sweeney, E. 1994, Fuzzy knowledge-based approach to treating uncertainty in inventory,
Computer Integrated Manufacturing Systems, vol. 7, no. 3, pp. 147-152.
Rachamadugu, R. and Stecke, K. E. 1988, Classification and review of FMS scheduling procedures, Working paper # 481 c, The University of Michigan, Ann Arbor.
Rachamadugu, R. and Stecke, K. E. 1994, Classification and review of FMS scheduling procedures,
Production Planning and Control, vol. 5, no. 1, pp. 2-20.
Ramasesh, R. 1990, Dynamic job shop scheduling: a survey of simulation research, Omega International
Journal of Management Science, vol. 18, no. 1, pp. 43-57.
Raoot, A. D. and Rakshit, A. 1991, A fuzzy approach to facilities lay-out planning, International Journal
of Production Research, vol. 29, no. 4, pp. 835-857.
Saaty, T. L. 1975, Hierarchies and priorities-eigenvalue analysis, internal report, University of Pennsyl- vania, Wharton School, Philadelphia, PA.
Saaty, T. L. 1977, A scaling method for priorities in hierarchical structures, Journal of Mathematical
Psychology, vol. 15, pp. 234-281.
Saaty, T. L. 1980, The Analytic Hierarchy Process, McGraw-Hill, New York.
Saaty, T. L. 1990, How to make a decision: the analytic hierarchy process, European Journal of Operational
Research, vol. 48, no. 1, pp. 9-26.
Saaty, T. L. and Vargas, L. G. 1987, Uncertainty and rank order in the Analytic Hierarchy Process, European
Journal of Operational Research, vol. 32, no. 3, pp. 107-117.
Singh, R. and Shivakumar, R. 1990, METEX — an expert system for machining planning, International
environment, 5th International Conference on System Research, Information and Cybernetics, Baden- Baden, Germany, pp. 1-7.
Wilhelm, W. E. and Shin, H. M. 1985, Effectiveness of alternate operations in a flexible manufacturing system, International Journal of Production Research, vol. 23, no. 1, pp. 65-79.
Yager, R. R. 1978, Fuzzy decision making including unequal objectives, Fuzzy Sets and Systems, vol. 1, pp. 87-95.
Yang, K. K. and Sum, C. C. 1994, A comparison of job dispatching rules using a total cost criterion,
International Journal of Production Research, vol. 32, no. 4, pp. 807-820.
Zadeh, L. A. 1965, Fuzzy sets, Information and Control, vol. 8, pp. 338-353.
For Further Information
Jamshidi, M., Vadaiee, N. and Ross T. J. 1993, Fuzzy Logic and Control: Software and Hardware Applications, Prentice-Hall, Englewood Cliffs, NJ.
Parsaei, H. R. 1995, Design and Implementation of Intelligent Manufacturing Systems: From Expert Systems,
Neural Networks, to Fuzzy Logic, Prentice-Hall, Englewood Cliffs, NJ.