General variable neighborhood search for the parallel machine scheduling problem with two common servers

Abstract We address in this paper the parallel machine scheduling problem with a shared loading server and unloading server. Each job has to be loaded by before being processed on one of available machines unloaded immediately after its processing. The objective function involves minimization overall completion time, known as makespan. This important raises flexible manufacturing systems, automated material handling, healthcare, many other industrial fields, been little studied up now. To date, research it focused case two machines. regular is considered. A mixed integer programming formulation based time variables suggested solve small-sized instances problem. Due $$\mathcal{NP}\mathcal{}$$ NP -hardness, we propose greedy heuristics loading, respectively unloading, waiting an efficient General Variable Neighborhood Search (GVNS) algorithm. In computational experiments, proposed methods are compared using 120 new publicly instances. It turns out that, GVNS initial solution-finding mechanism significantly outperforms approaches.