Logic-based Benders decomposition for additive manufacturing scheduling on unrelated parallel machines

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Authors: Jianzhong Chen, Wenjing Ma, Mingyue Sun, Zhiheng Zhao
Cited by: 1
References: 39

Abstract

Abstract Additive manufacturing (AM), also known as 3D printing, offers innovative solutions for customized production. This paper addresses an AM scheduling problem on unrelated parallel machines that considers different part release times. A mixed integer linear programming (MILP) model aimed at minimizing makespan is developed, enhanced by valid inequalities and symmetry-breaking constraints. We propose a logic-based Benders decomposition (LBBD) algorithm to divide the problem into a master problem (MP), which determines part assignment and grouping into batches, and multiple subproblems (SPs) that sequence the batches on each AM machine. An earliest release date (ERD) rule is introduced to quickly solve subproblems. Three feasibility cuts and two optimality cuts are proposed and combined into eight types of cuts for the master problem. In addition, a new heuristic is developed to quickly obtain an upper bound of the problem. Computational results across various instance sizes demonstrate the performance of the proposed LBBD algorithm, as well as the effectiveness of the proposed symmetry-breaking constraints and various types of cuts.

Fields of Study & Subjects

Additive Manufacturing and 3D Printing Technologies Manufacturing Process and Optimization Optimization and Packing Problems

Publication details

Journal / source
Annals of Operations Research
Publisher
Springer Science and Business Media LLC
Volume
358
Issue
3
Pages
1169–1198
Publication date
16 February 2026
Language
EN