Viewing scheduling as an opportunistic problem-solving process
Annals of Operations Research
The single machine early/tardy problem
Management Science
A branch-and-bound algorithm for the single machine earliness and tardiness scheduling problem
Computers and Operations Research
The harpy speech recognition system.
The harpy speech recognition system.
The argos image understanding system.
The argos image understanding system.
Constraint-directed search: a case study of job-shop scheduling
Constraint-directed search: a case study of job-shop scheduling
Improved heuristics for the early/tardy scheduling problem with no idle time
Computers and Operations Research
Order acceptance with weighted tardiness
Computers and Operations Research
Minimizing total earliness and tardiness on a single machine using a hybrid heuristic
Computers and Operations Research
Computers and Industrial Engineering
Computers and Operations Research
Computers and Operations Research
Computers and Industrial Engineering
Computers and Industrial Engineering
Beam search for the longest common subsequence problem
Computers and Operations Research
An effective heuristic for flexible job-shop scheduling problem with maintenance activities
Computers and Industrial Engineering
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In this paper, we present filtered and recovering beam search algorithms for the single machine earliness/tardiness scheduling problem with no idle time, and compare them with existing neighbourhood search and dispatch rule heuristics. Filtering procedures using both priority evaluation functions and problem-specific properties have been considered.The computational results show that the recovering beam search algorithms outperform their filtered counterparts, while the priority-based filtering procedure proves superior to the rules-based alternative. The best solutions are given by the neighbourhood search algorithm, but this procedure is computationally intensive and can only be applied to small or medium size instances. The recovering beam search heuristic provides results that are close in solution quality and is significantly faster, so it can be used to solve even large problems.