A hybrid discrete teaching-learning based meta-heuristic for solving no-idle flow shop scheduling problem with total tardiness criterion

DOI10.1016/j.cor.2018.02.003zbMath1391.90317OpenAlexW2792554292MaRDI QIDQ1652608

Dechang Pi, Zhongshi Shao, Weishi Shao

Publication date: 11 July 2018

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2018.02.003

zbMATH Keywords

reinforcement learningmeta-heuristictotal tardinessdiscrete learning phasediscrete teaching phaseno-idle flow shop scheduling problem

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (6)

Two-machine flow-shop scheduling to minimize total late work: revisited ⋮ An improved water wave optimization algorithm with the single wave mechanism for the no-wait flow-shop scheduling problem ⋮ Metaheuristics with restart and learning mechanisms for the no-idle flowshop scheduling problem with makespan criterion ⋮ MILP-based local search procedures for minimizing total tardiness in the no-idle permutation flowshop problem ⋮ A branch-and-bound approach to the no-idle flowshop scheduling problem ⋮ A new iterated greedy algorithm for no-idle permutation flowshop scheduling with the total tardiness criterion

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