Single machine scheduling to minimize total weighted late work: a comparison of scheduling rules and search algorithms

Authors:
R. Bryan Kethley;Bahram Alidaee
Affiliations:
Department of Management and Marketing, Jennings A. Jones College of Business, Middle Tennessee State University, MTSU P.O. Box X173, Murfreesboro, TN;Department of Management and Marketing, School of Business Administration, University of Mississippi, University, MS
Venue:
Computers and Industrial Engineering
Year:
2002

Citing 3
Cited 3

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Abstract

In this research the problem of scheduling n jobs to minimize the Total Weighted Late Work (TWLW) is evaluated within the single machine context. As the problem complexity increases, so does the solution complexity, and often the objective is to identify a heuristic or algorithm that may return a near optimal solution. Various scheduling rules, heuristics and algorithms, including the weighted shortest processing rule, a variation of the modified due date rule, a genetic algorithm, neighborhood job search, and space smoothing with neighborhood job search; are empirically evaluated using different parameters to determine the utility of each approach.