Scheduling in a sequence dependent setup environment with genetic search
Computers and Operations Research - Special issue on genetic algorithms
Constraint-Based Scheduling
An Iterated Dynasearch Algorithm for the Single-Machine Total Weighted Tardiness Scheduling Problem
INFORMS Journal on Computing
Computers and Operations Research
Enhancing Stochastic Search Performance by Value-Biased Randomization of Heuristics
Journal of Heuristics
Earliness-tardiness scheduling with setup considerations
Computers and Operations Research
Non-wrapping order crossover: an order preserving crossover operator that respects absolute position
Proceedings of the 8th annual conference on Genetic and evolutionary computation
An ant colony optimization for single-machine tardiness scheduling with sequence-dependent setups
Computers and Operations Research
Enhancing Lagrangian Dual Optimization for Linear Programs by Obviating Nondifferentiability
INFORMS Journal on Computing
Computers and Operations Research
Computers and Operations Research
Expert Systems with Applications: An International Journal
New Exact Algorithms for One-Machine Earliness-Tardiness Scheduling
INFORMS Journal on Computing
HIS '09 Proceedings of the 2009 Ninth International Conference on Hybrid Intelligent Systems - Volume 01
An exact algorithm for single-machine scheduling without machine idle time
Journal of Scheduling
Journal of Intelligent Manufacturing
Computers and Operations Research
A GRASP based on DE to solve single machine scheduling problem with SDST
Computational Optimization and Applications
Dynasearch for the earliness-tardiness scheduling problem with release dates and setup constraints
Operations Research Letters
Fast neighborhood search for the single machine total weighted tardiness problem
Operations Research Letters
Operations Research Letters
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This study proposes an exact algorithm for the single-machine total weighted tardiness problem with sequence-dependent setup times. The algorithm is an extension of the authors' previous algorithm for the single-machine scheduling problem without setup times, which is based on the SSDP (Successive Sublimation Dynamic Programming) method. In the first stage of the algorithm, the conjugate subgradient algorithm or the column generation algorithm is applied to a Lagrangian relaxation of the original problem to adjust multipliers. Then, in the second stage, constraints are successively added to the relaxation until the gap between lower and upper bounds becomes zero. The relaxation is solved by dynamic programming and unnecessary dynamic programming states are eliminated to suppress the increase of computation time and memory space. In this study a branching scheme is integrated into the algorithm to manage to solve hard instances. The proposed algorithm is applied to benchmark instances in the literature and almost all of them are optimally solved.