Integrating energy management systems and renewable energy sources in green warehouses: the energy-aware green sequencing and routing problem

Warehouse operations are increasingly scrutinised for their contribution to greenhouse gas emissions. The adoption of Electric Vehicles (EVs), renewable energy sources, and Energy Storage Systems (ESS) represents an energy-efficient strategy to reduce the environmental impact of warehouses. In this context, designing an Energy Management System (EMS) is crucial to optimising energy use and enhancing sustainability. This paper proposes a novel framework that jointly schedules daily warehouse operations (including sequencing of storage and retrieval tasks, assigning tasks to fuel-based vehicles or EVs, and vehicle routing) and manages energy flows among photovoltaic panels, ESS, power grid, and EV charging station. A Mixed Integer Linear Programming model is proposed to address this integrated planning problem. Computational experiments in realistic situations under sunny and cloudy weather conditions demonstrate the effectiveness of the proposed formulation. The results highlight the importance of integrating renewables, EMS, and warehouse operations to reduce costs and support sustainable warehouse operations. Moreover, a very fast matheuristic algorithm is proposed to efficiently solve large and real-scale instances. Dedicated experiments on a real case study confirm the capability of the approach to deliver fast and high-quality solutions in industrial case scenarios.