Priority rules for job shops with weighted tardiness costs
Management Science
A survey of algorithms for the single machine total weighted tardiness scheduling problem
Discrete Applied Mathematics - Southampton conference on combinatorial optimization, April 1987
Design of Iterated Local Search Algorithms
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
An Iterated Dynasearch Algorithm for the Single-Machine Total Weighted Tardiness Scheduling Problem
INFORMS Journal on Computing
Mathematical Programming: Series A and B
Computers and Operations Research
Computers and Operations Research
Interval-indexed formulation based heuristics for single machine total weighted tardiness problem
Computers and Operations Research
Minimizing total tardiness on a single machine with controllable processing times
Computers and Operations Research
Computers and Operations Research
New Precedence Theorems for One-Machine Weighted Tardiness
Mathematics of Operations Research
Time-Indexed Formulations and the Total Weighted Tardiness Problem
INFORMS Journal on Computing
Principles of Sequencing and Scheduling
Principles of Sequencing and Scheduling
Computers and Operations Research
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Earlier research by Kanet [11] has provided a number of new theorems for deciding precedence between pairs of jobs for 1||@Sw"jT"j. The theorems supplant those of Rinnooy Kan, Lageweg, and Lenstra [16]. Presented here are the results of an analysis of the marginal benefit these new theorems provide over the earlier versions of Rinnooy Kan et al. Results show that the new theorems can provide noteworthy improvements in the ability to discover precedence relations between job pairs. For a large set of problem instances the new theorems uncovered up to 8% more precedence relations than the original theorems of Rinnooy Kan et al. The improvement in the productivity in discovering precedence relations shows to be dependent on the coefficient of variation of the distribution of job weights. Logical application of the theorems is to include them in search procedures and/or heuristic approaches to 1||@Sw"jT"j. One such heuristic based on the theorems is provided here in which the solutions to a large set of sample problems are within 8-12% of the optimum.