A fast Reoptimization approach for the dynamic technician routing and scheduling problem

The Technician Routing and Scheduling Problem (TRSP) consists in routing staff to serve requests for service, taking into account time windows, skills, tools, and spare parts. Typical applications include maintenance operations and staff routing in telecoms, public utilities, and in the health care industry. In this paper we tackle the Dynamic TRSP (D-TRSP) in which new requests appear over time. We propose a fast reoptimization approach based on a parallel Adaptive Large Neighborhood Search (RpALNS) able to achieve state-of-the-art results on the Dynamic Vehicle Routing Problem with Time Windows. In addition, we solve a set of randomly generated D-TRSP instances and discuss the potential gains with respect to a heuristic modeling a human dispatcher solution

Chopping Down Trees vs. Sharpening the Axe – Balancing the Development of BPM Capabilities with Process Improvement

The management and improvement of business processes is an evergreen topic of organizational design. With many techniques and tools for process modeling, execution, and improvement being available, research pays progressively more attention to the organizational impact of business process management (BPM) and the development of BPM capabilities. Despite knowledge about the capabilities required for successful BPM, there is a lack of guidance on how these BPM capabilities should be developed and balanced with the improvement of individual business processes. As a first step to address this research gap, we propose a decision model that enables valuating and selecting BPM roadmaps, i.e., portfolios of scheduled projects with different effects on business processes and BPM capabilities. The decision model is grounded in the literature related to project portfolio selection, process performance measurement, and value-based management. We also provide an extensive demonstration example to illustrate how the decision model can be applied