Deterministic and random single machine sequencing with variance minimization
Operations Research
Sequencing with earliness and tardiness penalties: a review
Operations Research
Minimizing single-machine completion time variance
Management Science
Tabu search for a class of single-machine scheduling problems
Computers and Operations Research
A branch and bound algorithm to minimize completion time variance on a single processor
Computers and Operations Research
Completion time variance minimization on a single machine is difficult
Operations Research Letters
Proof of a conjecture of Schrage about the completion time variance problem
Operations Research Letters
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This paper illustrates that by exploiting the structure of hard combinatorial optimization problems, efficient local search schemes can be designed that guarantee performance in solution quality and computational time. A two-phase local search algorithm is developed and applied to the permutation flow shop scheduling problem, with the objective of minimizing the completion time variance. New and significant analytical insights necessary for effectively solving the permutation flow shop problem are also presented and used in this research. Computational results indicate that for test problems, the local search obtained optimal solutions for many instances, within few seconds of CPU time. For other benchmark problems with jobs between 50 and 100, the proposed algorithm, ADJ-Reduced improved the existing best known values within a practical time frame.