A cooperative team orienteering optimisation model and a customised resolution metaheuristic
针对节能服务公司中异构维修团队的服务调度问题，建模为带时间窗、资质和同步约束的合作定向越野问题，提出一种插入式启发并嵌入自适应大邻域搜索算法，通过真实数据验证其鲁棒性和管理启示。
Workforce routing optimisation is an essential management task to achieve customer satisfaction and minimise costs in service-providing companies. A typical problem for an energy-saving company (ESCo) is to optimise the provisioning of maintenance services for the contracted buildings through a fleet of heterogeneous maintenance staff. This problem is modelled as a cooperative orienteering problem with time windows, operator qualification, and synchronisation constraints. A novel insertion heuristic is proposed and embedded in an adaptive large neighbourhood search algorithm and it is tested against a state-of-the-art algorithm using real-world data. The comparative study demonstrates the potential of the heuristic and a sensitivity analysis shows its robustness, focusing on time window length variation, and the number of synchronisation requirements. We consider managerial insights supported by results and concerns, e.g., the employment of further technicians to increase the number of served facilities. The proposed model and algorithm apply to similar problems as well.