A multi-objective evolutionary algorithm guided by directed search for dynamic scheduling

DOI10.1016/j.cor.2016.04.024zbMath1391.90326OpenAlexW2346181637MaRDI QIDQ1652172

Yaochu Jin, Feng Liu, Du-Juan Wang

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.2016.04.024

zbMATH Keywords

predictiondynamic schedulinghistorical informationdirected search strategydynamic evolutionary multi-objective optimization

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (5)

A tardiness-augmented approximation scheme for rejection-allowed multiprocessor rescheduling ⋮ A dynamic multi-objective evolutionary algorithm based on intensity of environmental change ⋮ Predictive-reactive strategy for identical parallel machine rescheduling ⋮ A novel quantile-guided dual prediction strategies for dynamic multi-objective optimization ⋮ Rescheduling due to machine disruption to minimize the total weighted completion time

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