An adaptive hybrid neighbourhood search algorithm for order acceptance and batch scheduling problem in additive manufacturing

2025/06/11 by Zhaofang Mao, Teng Cao, Enyuan Fu +2 · 1 citation
Engineering · #Advanced Manufacturing and Logistics Optimization #Scheduling and Optimization Algorithms #Manufacturing Process and Optimization

paper · doi:10.1080/00207543.2025.2516189

Abstract

This paper addresses the order acceptance and batch scheduling problem on a single machine in the additive manufacturing environment, in which the manufacturer must make both order acceptance and scheduling decisions to maximise total net profit. We first present the MILP model for the problem. Then, due to the inherent complexity of the problem, we develop an adaptive hybrid neighbourhood search (AHNS) algorithm to obtain high-quality solutions that satisfy all technical constraints. To assess the performance of the AHNS algorithm across various classes of instances, we analyze the sensitivity of the experimental parameters and conduct extensive computational experiments. The computational results show that the AHNS algorithm can obtain high-quality solutions in a shorter time compared with several other approaches.

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• Logic-based Benders decomposition for integrated order acceptance, distributed heterogeneous factories, inventory, and hub-spoke delivery scheduling under make-to-order products

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