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Related Experiment Video

Updated: Feb 28, 2026

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An Iterated Greedy Heuristic for Mixed No-Wait Flowshop Problems.

Yamin Wang, Xiaoping Li, Ruben Ruiz

IEEE Transactions on Cybernetics

|June 11, 2017

Summary

This summary is machine-generated.

This study introduces a novel iterated greedy algorithm for the mixed no-wait flowshop problem, optimizing production schedules. The new algorithm significantly outperforms existing methods in minimizing makespan for complex manufacturing scenarios.

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Area of Science:

Operations Research
Industrial Engineering
Manufacturing Systems

Background:

The mixed no-wait flowshop problem combines traditional flowshop and no-wait constraints, presenting complex scheduling challenges.
This problem is a generalization of permutation flowshop and no-wait flowshop, with broad real-world applicability in manufacturing and logistics.

Purpose of the Study:

To address the makespan minimization objective for the mixed no-wait flowshop problem.
To develop and evaluate an efficient algorithmic approach for this complex scheduling problem.

Main Methods:

A mathematical model was formulated for the mixed no-wait flowshop problem.
A speed-up makespan calculation procedure was designed.
A modified iterated greedy algorithm was developed, incorporating initialization, destruction, reconstruction, and local search components.
Insertion heuristics were applied during solution construction and reconstruction phases to enhance intensification.

Main Results:

The proposed iterated greedy algorithm demonstrated superior performance compared to five existing algorithms.
The algorithm achieved the best results on adapted Taillard benchmark instances for makespan minimization.
Parameter calibration and component analysis confirmed the effectiveness of the proposed method.

Conclusions:

The developed iterated greedy algorithm is highly effective for makespan minimization in mixed no-wait flowshop scheduling.
This research provides a valuable contribution to solving complex scheduling problems with practical industrial implications.