Work

Permutation Flow Shop Scheduling Optimization with Batch Heat Treatment for Gear Manufacturing

Year: 2026

Type: conference-paper

Abstract: In gear manufacturing, workpieces pass through forging, turning, hobbing, carburizing and quenching, and finish grinding. The carburizing furnace is a batch processing machine (BPM) with fixed cycle time, intrinsically coupling discrete stages upstream and downstream. This paper studies the permutationconstrained flow-shop scheduling problem with embedded batch processing (PFSP-BPM) to isolate the sequencing-batching coupling. A mixed-integer linear programming (MILP) model is developed to jointly minimize makespan and total carbon emissions; explicit linearization renders it directly solvable by commercial solvers. Correctness is verified via exhaustive enumeration on 16 instances and$\varepsilon$-constraint Pareto-front analysis. Experiments reveal a parameter-dependent Pareto trade-off, while exact optimality becomes difficult to certify beyond$n=8$. Decoupledbaseline results further show that permutation and batching decisions are structurally non-separable: optimizing either in isolation forfeits synergy gains of$4.7 \%-7.7 \%$.

Source: International Conference on Data-driven Optimization of Complex Systems (DOCS)

DOI: 10.1109/docs70981.2026.11698620

Authors: Bixian Song, Lingchong Zhong, Xing Guo, Zaixing Sun, Xunyong Yang, Hui Liu

Institutions: Gannan University of Science and Technology, Peng Cheng Laboratory

Language: English

Topic: Scheduling and Optimization Algorithms

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7214769413

FWCI:

Cites: 19

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Related to: 10