Deterministic and random single machine sequencing with variance minimization
Operations Research
On the minimization of completion time variance with a bicriteria extension
Operations Research
Computers and Operations Research
Minimizing single-machine completion time variance
Management Science
Hierarchical minimization of completion time variance and makespan in jobshops
Computers and Operations Research
Job scheduling to minimize the weighted waiting time variance of jobs
Computers and Industrial Engineering
Job scheduling methods for reducing waiting time variance
Computers and Operations Research
Completion time variance minimization in single machine and multi-machine systems
Computers and Operations Research
Hierarchical minimization of completion time variance and makespan in jobshops
Computers and Operations Research
Minimizing job completion time variance for service stability on identical parallel machines
Computers and Industrial Engineering
An efficient local search for minimizing completion time variance in permutation flow shops
Computers and Operations Research
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In this paper we discuss a single machine scheduling problem with the objective of minimizing the variance of job completion times. The CTV problem has been proved to be NP hard (Oper. Res. Lett. 14 (1993) 49) and no polynomial time algorithm exists to find an optimal solution for CTV minimization on single machine. Hence enumerative techniques and heuristics are used to get optimal and near optimal solutions, respectively. We present a branch and bound algorithm and extend the same algorithm to generate epsilon optimal solutions for large sized problems (i.e., number of jobs 30). The algorithm has been computationally tested, with randomly generated problems involving up to 100 jobs, using a personal computer (PC) with a 64 MB RAM capacity. The computational time required for generating optimal solutions are in few seconds for problems with jobs between 25 and 30. The performance of the branch and bound algorithm is compared with the pseudo-polynomial algorithm (Oper. Res. 40 (1992) 1148) for small sized problems. For problems with greater number of jobs, the epsilon optimal solutions obtained using branch and bound algorithm are compared with results of simulated annealing (Single machine scheduling with some non-regular objectives, M.S. Thesis, IIT Madras, 1997), tabu search (Proceedings of Operations Management Conference, IIT Madras, 2000) and heuristic proposed by Manna and Prasad (Eur. J. Oper. Res. 114 (1999) 411).