This study addresses the integration of energy-efficient robotic disassembly with vehicle routing within a single unified optimization model. The disassembly process is represented through a transformed AND/OR graph, which captures the precedence relationships and alternative disassembly sequences of end-of-life products. The proposed framework links disassembly decisions directly to the transportation of recovered parts, where the energy consumption of robotic disassembly operations is accounted for alongside routing costs. This is the first study to incorporate robot energy consumption within an integrated disassembly and vehicle routing system, constituting the main novelty of this work. A mixed-integer programming formulation is developed that jointly determines task allocations, robot assignments, disassembly sequences derived from the transformed AND/OR graph, and vehicle routes. The objective minimizes total cost, capturing the trade-off between the energy efficiency of disassembly operations and the routing of recovered components. By coupling these two traditionally separate decision domains, the model enables coordinated planning that reduces overall energy consumption while satisfying routing and demand requirements. Computational experiments demonstrate the effectiveness of the proposed approach and provide managerial insights into how energy-aware disassembly decisions influence routing structures and total system cost. The results highlight the value of jointly optimizing disassembly and distribution activities for sustainable remanufacturing and reverse logistics systems.

Keywords

Robotic disassembly; Energy efficiency; Vehicle routing problem; Sustainable remanufacturing