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August 22, 2025SustainabilityOpen Access

Enhanced Optimization Strategies for No-Wait Flow Shop Scheduling with Sequence-Dependent Setup Times: A Hybrid NEH-GRASP Approach for Minimizing the Total Weighted Flow Time and Energy Cost

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HGRASP consistently achieved near-optimal solutions, indicating a high-performance level compared to traditional methods.
Statistical analysis showed significant performance differences across MILP, GRASP, and HGRASP with χ2 = 46.75, p = 7.04 × 10−11.
The proposed hybrid approach integrates mixed integer linear programming and heuristics to enhance scheduling efficiency.
While MILP guarantees optimal solutions, its practical efficiency is limited, making HGRASP a preferred alternative.

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Implication

This analysis reveals significant improvements in total weighted flow time and energy cost in flow shop scheduling, indicating HGRASP's effectiveness over traditional MILP methods.

Cite This Study

Mimouni et al. (2025) studied this question.

synapsesocial.com/papers/68af5707ad7bf08b1eadd914 https://doi.org/10.3390/su17177599

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Implication

This analysis reveals significant improvements in total weighted flow time and energy cost in flow shop scheduling, indicating HGRASP's effectiveness over traditional MILP methods.

Enhanced Optimization Strategies for No-Wait Flow Shop Scheduling with Sequence-Dependent Setup Times: A Hybrid NEH-GRASP Approach for Minimizing the Total Weighted Flow Time and Energy Cost

Key Points

Discussion

Implication

Cite This Study

Enhanced Optimization Strategies for No-Wait Flow Shop Scheduling with Sequence-Dependent Setup Times: A Hybrid NEH-GRASP Approach for Minimizing the Total Weighted Flow Time and Energy Cost

Key Points

Discussion

Implication

Cite This Study

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