Metaheuristics for the single machine weighted quadratic tardiness scheduling problem

This paper considers the single machine scheduling problem with weighted quadratic tardiness costs. Three metaheuristics are presented, namely iterated local search, variable greedy and steady-state genetic algorithm procedures. These address a gap in the existing literature, which includes branch-a...

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Vydáno v:Computers & operations research Ročník 70; s. 115 - 126
Hlavní autoři: Gonçalves, Tomás C., Valente, Jorge M.S., Schaller, Jeffrey E.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Elsevier Ltd 01.06.2016
Pergamon Press Inc
Témata:
Branch & bound algorithms
Computation
Genetic algorithm
Genetic algorithms
Heuristic
Heuristic methods
Iterated local search
Iterative methods
Mathematical models
Metaheuristics
Operations research
Optimization
Production scheduling
Quadratic programming
Scheduling
Searching
Single machine
Studies
Variable greedy
Weighted quadratic tardiness
Metaheuristics
Genetic algorithm
Scheduling
Variable greedy
Weighted quadratic tardiness
Single machine
Iterated local search
ISSN:0305-0548, 1873-765X, 0305-0548
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Shrnutí:This paper considers the single machine scheduling problem with weighted quadratic tardiness costs. Three metaheuristics are presented, namely iterated local search, variable greedy and steady-state genetic algorithm procedures. These address a gap in the existing literature, which includes branch-and-bound algorithms (which can provide optimal solutions for small problems only) and dispatching rules (which are efficient and capable of providing adequate solutions for even quite large instances). A simple local search procedure which incorporates problem specific information is also proposed. The computational results show that the proposed metaheuristics clearly outperform the best of the existing procedures. Also, they provide an optimal solution for all (or nearly all, in the case of the variable greedy heuristic) the smaller size problems. The metaheuristics are quite close in what regards solution quality. Nevertheless, the iterated local search method provides the best solution, though at the expense of additional computational time. The exact opposite is true for the variable greedy procedure, while the genetic algorithm is a good all-around performer. •Metaheuristics for single machine weighted quadratic tardiness scheduling.•Address gap in existing literature (B&B, dispatching rules).•Simple local search with problem specific information.•Large and diversified set of instances.•Proposed metaheuristics outperform existing procedures in solution quality.
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ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2016.01.004