Analysis and optimization of mobile business processes
Mobility of workers and business processes rapidly gains the attention of businesses and business analysts. A wide variety of definitions exists for mobile business processes. This work considers a type of business processes concerned with the maintenance of distributed technical equipment as, e.g., telecommunication networks, utility networks, or professional office gear. Executing the processes in question, workers travel to the location where the equipment is situated and perform tasks there. Depending on the type of activities to be performed, the workers need certain qualifications to fulfill their duty. Especially in network maintenance processes, activities are often not isolated but depend on the parallel or subsequent execution of other activities at other locations. Like every other economic activity, the out- lined mobile processes are under permanent pressure to be executed more efficiently. Since business process reengineering (BPR) projects are the common way to achieve process improvements, business analysts need methods to model and evaluate mobile business processes. Mobile processes challenge BPR projects in two ways: (i) the process at- tributes introduced by mobility (traveling, remote synchronization, etc.) complicate process modeling, and (ii) these attributes introduce process dynamics that prevent the straightforward prediction of BPR effects. This work solves these problems by developing a modeling method for mobile processes. The method allows for simulating mobile processes considering the mobility attributes while hiding the complexity of these attributes from the business analysts modeling the processes. Simulating business processes requires to assign activites to workers, which is called scheduling. The spatial distribution of activities relates scheduling to routing problems known from the logistics domain. To provide the simula- tor with scheduling capabilities the according Mobile Workforce Scheduling Problem with Multitask-Processes (MWSP-MP) is introduced and analyzed in-depth. A set of neighborhood operators was developed to allow for the application of heuristics and meta-heuristics to the problem. Furthermore, methods for generating start solutions of the MWSP-MP are introduced. The methods introduced throughout this work were validated with real-world data from a German utility. The contributions of this work are a reference model of mobile work, a business domain independent modeling method for mobile business processes, a simulation environment for such processes, and the introduction and analysis of the Mobile Workforce Scheduling Problem with Multitask-Processes.
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