Efficient algorithms for the bucket wheel reclaimer scheduling problem with sequence-dependent setup times

The effective management of resources in bulk ports presents substantial challenges, prominently concerning the intricate scheduling of bucket wheel reclaimers (BWRs). These essential machines play a vital role in the reclamation of dry bulk materials, facilitating their loading onto vessels via ship-loaders. The research at hand centers around the BWR scheduling problem, wherein the sequence-dependent setup times and eligibility restrictions of these machines are duly considered. The optimization of BWR schedules holds direct implications for terminal throughput, which is a paramount performance metric for dry bulk terminals. The primary objective revolves around the minimization of total completion times, as it pertains to enhancing the overall efficiency and productivity of the terminal operations. For this $$\mathcal{N}\mathcal{P}$$ N P -hard problem, we present a novel mixed-integer linear programming (MILP) formulation based on one commodity variables. Additionally, we develop three efficient greedy heuristics, each with three variants, resulting in a total of nine heuristics, to solve large-sized instances of the problem. Furthermore, an efficient general variable neighborhood search (GVNS) algorithm is proposed to improve the quality of the heuristic solutions. Through extensive computational experiments, we assess the effectiveness of the proposed methods. The results demonstrate that the developed greedy heuristics efficiently yield high-quality approximation solutions for solving large-scale instances of the problem. Moreover, the application of the GVNS algorithm further enhances the solutions obtained through the heuristics, leading to an improvement in scheduling efficiency.