An adaptive hybrid neighbourhood search algorithm for order acceptance and batch scheduling problem in additive manufacturing
针对增材制造中单机环境下的订单接受与分批调度问题，提出自适应混合邻域搜索算法，以最大化总净利润，实验表明该算法能在更短时间内获得高质量解。
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.