Clustering and genetic algorithm based hybrid flowshop scheduling with multiple operations

DOI10.1155/2014/167073zbMath1407.90189OpenAlexW2147198753WikidataQ59063416 ScholiaQ59063416MaRDI QIDQ1717811

Yingfeng Zhang, Sichao Liu, ShuDong Sun

Publication date: 8 February 2019

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2014/167073

Mathematics Subject Classification ID

Deterministic scheduling theory in operations research (90B35)

Related Items (1)

A Pareto-based adaptive variable neighborhood search for biobjective hybrid flow shop scheduling problem with sequence-dependent setup time

Cites Work

• A multi-stage parallel-processor flowshop problem with minimum flowtime
• A hybrid three-stage flowshop problem: Efficient heuristics to minimize makespan
• Performance of scheduling algorithms for no-wait flowshops with parallel machines
• Hybrid flow-shop scheduling problems with multiprocessor task systems.
• Job-shop scheduling with blocking and no-wait constraints
• Multiprocessor task scheduling in multistage hybrid flow-shops: an ant colony system approach
• Analysis of Classes of Heuristics for Scheduling a Two-Stage Flow Shop with Parallel Machines at One Stage

This page was built for publication: Clustering and genetic algorithm based hybrid flowshop scheduling with multiple operations