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Our project addresses the question how to automatically and simultaneously assign staff to workstations and generate optimised working time models on the basis of fluctuating personnel demand while taking into account practical constraints. Two fundamentally different solution approaches, a specialized constructive heuristic (commercial) and a hybrid metaheuristic (the evolution strategy) that integrates a repair heuristic to remove contraint violations are compared on a complex real-world problem from a retailer. The hybrid approach clearly outperforms the tailored constructive method. Taken together with our similar findings on a related staff scheduling problem from logistics this result suggests that the evolution strategy, despite its original focus on continuous parameter optimisation, is a powerful tool in combinatorial optimisation and deserves more attention. Moreover, hybridising a metaheuristic with a problem-specific repair heuristic seems a useful approach of resolving the conflict between domain-specific characteristics of a realworld problem and the desire to employ generic optimisation techniques, at least in the domain of workforce management.

Retail is traditionally labour-intensive. Demand-oriented workforce management has great significance due to the amount of competition which enforces a strict cost management while keeping a good service level. Thus, highly flexible working time models are of particular importance. Our project addresses the question how to automatically and simultaneously assign staff to workstations and generate optimised working time models under constraints and on the basis of fluctuating personnel demand. The planning is completed for an entire year in order to assess adapted versions of the evolution strategy and particle swarm optimisation. A commercial constructive method is used as benchmark.

Today many companies face the challenge of matching highly-skilled professionals to high-end positions in large organizations and human deployment agencies. Non-accurate matches in these businesses can result in significant monetary losses and other negative effects. Unlike traditional Workforce Management (WM) problems such as shift scheduling, highly-skilled employees are professionally distinguishable from each other and hence non-interchangeable. Therefore, the techniques used for shift-scheduling can't be applied to the highly-skilled WM domain. Our work focuses on providing a Constraint Programming solution for supporting the assignment of highly-skilled professionals. Our experience shows that CP is well adapted to this problem. CP supports very well the underlying constraints. In addition, the rich expressive language supported by CP allows us to provide a convenient mechanism for changing and adding new matching and preference constraints. Based on this technology, we have built a tool that is currently being used by IBM service organizations and provides strong business results.

In this work we introduce a general model for the description of mobile workforce environments In the context of Business Process reengineering projects such models are necessary to predict the outcome of the optimization efforts The model we propose is designed to be domain independent and can thus be utilized in BPR projects for any business domain incorporating mobile workforce systems.

Workforce management is comprised of several phases, such as working time model generation and personnel scheduling. The combination of these phases has significant potential, especially for volatile personnel demand. This article shows that the concepts for the automatic generation of working time models already used in retail can be transferred to personnel scheduling in the logistics industry. Through this, the assignment of personnel can be accurately adapted to personnel demand. The results suggest the use of heuristics, especially meta-heuristics such as the evolution strategy or constructive methods which are adapted to the problem at hand.

We show how model-based on-the-fly testing can be applied in the context of web applications using the NModel toolkit. The concrete case study is a commercial web-based positioning system called WorkForce Management (WFM) which interacts with a number of other services, such as billing and positioning, through a mobile operator. We describe the application and the testing, and discuss the test results.

In recent years, global telecommunication service providers are struggling to survive through service convergence, integration, and bundling. In these circumstances the telcos hope to maintain their network stable but catch up with the brand-new business trends. Therefore they also want to diagnose the process related to the network operations management and improve it into the optimum. In this paper, the flexible and reliable architecture of workforce management, which is part of the network operations management, will be studied as follows: First, we will mention the business process of workforce management related to service assurance in telecom sector. Second, we design and model the workforce management's activities according to the Business Process Management (BPM). And the specific implementation is discussed. By adopting the BPM, the network service providers can track and monitor their current status of workload, workforce. They can modify their workforce management into more easily integrated and process-based architecture.

Keeping sight of the enterprise's workforce strengthens the entire business by helping to avoid poor decision-making and lowering the risk of failure in problem-solving. It is critical for large-scale, global enterprises to have capabilities to quickly identify subject matter experts (SMEs) to staff teams or to resolve domain-specific problems. This requires timely understanding of the kinds of experience and expertise of the people in the firm for any given set of skills. Fortunately, a large portion of the information that is needed to identify SMEs and knowledge communities is embedded in many structured and unstructured data sources. Mining and understanding this information requires non-linear processes to interact with automated tools; along with visualizations of different interrelated data to enable exploration and discovery. This paper describes a visualization solution coupled with an interactive information analytics technique to facilitate the discovery and identification of workforce experience and knowledge community capacity.