HYBRID DECISION-MAKING IN FLOW SHOP SCHEDULING: CONTRASTING BB AND NEH WITH INTERVAL VALUED INTUITIONISTIC FUZZY DATA

Authors:

Rajvinder Kaur,Deepak Gupta,Sonia Goel,

DOI NO:

https://doi.org/10.26782/jmcms.2026.05.00011

Keywords:

Interval-Valued Intuitionistic Fuzzy Sets,Hybrid Flow Shop Scheduling,Score Function,Makespan,

Abstract

Scheduling problems represent a core challenge in the efficient management of industrial and service operations. Due to their structural complexity and significant practical relevance in both manufacturing and service sectors, Hybrid Flow Shop Scheduling Problems (HFSSPs) are widely recognized as NP-hard. Scheduling in contemporary manufacturing and production systems sometimes entails ambiguous and uncertain information, rendering classical deterministic methods less efficacious. This work presents a novel comparative analysis of the exact method Branch and Bound (BB) and heuristic algorithm Nawaz, Enscore, and Ham (NEH) for addressing the hybrid flow shop scheduling problem (HFSSP), where processing times are articulated via Interval-Valued Intuitionistic Fuzzy Sets (IVIFS). A ranking and scoring algorithm is utilised to convert IVIFS data into computationally manageable values, facilitating integration with BB and NEH methodologies. The results offer valuable insights for scheduling in uncertain and imprecise production environments, demonstrating how hybrid decision-making strategies that combine exact and heuristic methods can lead to more effective solutions.

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