The Weibull scheduling index for client driven manufacturing processes

This paper highlights a new dispatching rule based on an index developed from a modified two parameter Weibull probability distribution function. This new dispatching rule is named the Weibull Urgency Index (WUI), which uses the capability of the Weibull function's generation of unique curves to develop an index behavior based on job type. Hence, this unique index curve reflects how a job will behave within the queue. The paper describes in detail the development of this new heuristic function and it is compared to the well established Apparent Tardiness Cost (ATC) dispatching rule through a simulation study. The new index is tested in a stochastic environment where jobs arrive randomly and the processing time of the jobs is also not completely known.

[1]  Manuel D. Rossetti.  Simulation Modeling and Arena , 2015 .

[2]  Timothy I. Matis,et al.  A flexible dispatching rule for minimizing tardiness in job shop scheduling , 2013 .

[3]  Chandrasekharan Rajendran,et al.  Efficient dispatching rules for scheduling in a job shop , 1997 .

[4]  Ihsan Sabuncuoglu,et al.  A Load-based and Due-date-oriented Approach to Order Review/Release in Job Shops , 2000, Decis. Sci..

[5]  Tarik Çakar,et al.  Single machine scheduling with unequal release date using neuro-dominance rule , 2011, J. Intell. Manuf..

[6]  Jerald F. Lawless,et al.  Statistical Models and Methods for Lifetime Data. , 1983 .

[7]  Ari P. J. Vepsalainen.  Priority rules for job shops with weighted tardiness costs , 1987 .

[8]  P. Suganthan,et al.  A hybrid tabu search algorithm with an efficient neighborhood structure for the flexible job shop scheduling problem , 2011 .

[9]  Michael Pinedo,et al.  Scheduling: Theory, Algorithms, and Systems , 1994 .

[10]  B. Karimi,et al.  New dispatching rules to minimize rejection and tardiness costs in a dynamic flexible flow shop , 2009 .

[11]  Pedro M. Mateo,et al.  Production scheduling in a market-driven foundry: a mathematical programming approach versus a project scheduling metaheuristic algorithm , 2011 .

[12]  Massimo Paolucci,et al.  A new discrete particle swarm optimization approach for the single-machine total weighted tardiness scheduling problem with sequence-dependent setup times , 2009, Eur. J. Oper. Res..

[13]  Egon Balas,et al.  The Shifting Bottleneck Procedure for Job Shop Scheduling , 1988 .

[14]  Jorge M. S. Valente.  Improving the performance of the ATC dispatch rule by using workload data to determine the lookahead parameter value , 2007 .

[15]  V. Vinod,et al.  Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system , 2011 .

[16]  Philippe Baptiste,et al.  Dominance-based heuristics for one-machine total cost scheduling problems , 2008, Eur. J. Oper. Res..

[17]  Richard H. Deane,et al.  A Loading and Balancing Methodology for Job Shop Control , 1974 .

[18]  Mostafa Zandieh,et al.  Multi-objective scheduling of dynamic job shop using variable neighborhood search , 2010, Expert Syst. Appl..

[19]  Fariborz Jolai,et al.  Hierarchical production planning and scheduling in make-to-order environments: reaching short and reliable delivery dates , 2009 .

[20]  Chuen-Lung Chen,et al.  Bottleneck-based heuristics to minimize total tardiness for the flexible flow line with unrelated parallel machines , 2009, Comput. Ind. Eng..

[21]  Rubén Ruiz,et al.  The hybrid flow shop scheduling problem , 2010, Eur. J. Oper. Res..

[22]  Chester G. Chambers,et al.  Manufacturing Operations Manuscripts Published in the First 52 Issues of POM: Review, Trends, and Opportunities , 2009 .

[23]  Liang Gao,et al.  Evolving scheduling rules with gene expression programming for dynamic single-machine scheduling problems , 2010 .

[24]  George Casella,et al.  Statistical Inference Second Edition , 2007 .

[25]  George Q. Huang,et al.  Integrating order review/release and dispatching rules for assembly job shop scheduling using a simulation approach , 2011 .

[26]  Fuh-Der Chou,et al.  An experienced learning genetic algorithm to solve the single machine total weighted tardiness scheduling problem , 2009, Expert Syst. Appl..