Integrated inbound and inplant logistics scheduling of containers via heterogeneous material-handling resources

This study examines the integrated inbound and inplant logistics in transporting containers with automobile parts from docks to designated storage locations, referred to as marketplaces, within an automobile manufacturing facility. The movement of these containers relies on Material Handling Resources (MHRs) with heterogeneous capacities. Stemming from a real-life scenario encountered in a manufacturing plant, this research represents a pioneering effort in exploring the integration of inbound and inplant logistics and thus highlights the operational intricacies of assigning docks and scheduling inbound trucks, along with the allocation and scheduling of unloaded containers via MHRs simultaneously. A mixed integer linear programming (MILP) model for integrated inbound and inplant logistics is proposed to optimize the makespan for container transport from dock to marketplace. Consequently, the developed model ensures comprehensive tracking of container movement from the dock to their respective marketplaces and other characteristics not addressed before in literature. A comparative analysis between the integrated and sequential approaches is conducted to underscore the advantages of the new approach, which demonstrates that a sequential approach yields suboptimal outcomes. Additionally, an innovative technique, namely Divide-Fix, Fix-Optimize, and Overarching Generate-Optimize, is introduced. This method leverages heuristics, MILP and three adapted metaheuristics—Population-based Multi-start Simulated Annealing, Hybrid Harris Hawks Optimization, and Opposition-based Whale Optimization Algorithm—to address large-scale instances. Notably, the technique yields good solutions with an optimality gap within 3 % and exhibits a narrow confidence interval, indicating consistent and stable outcomes.