Scheduling IT Staff at a Bank: A Mathematical Programming Approach

Workforce scheduling is known as a complex and highly constraint problem. In the last few years the problem even become more complex due to the deregulation of laws limiting working times, flexibility and opening hours for shops at least in Germany. This paper describes an intelligent workforce scheduling component which shall be incorporated in a commercial workforce planning and scheduling system. Main points are the modelling of the workforce scheduling problem and a heuristic to provide a solution that regards the given hard and soft constraints.

2011 IEEE Symposium on Computational Intelligence in Scheduling (SCIS), 2011

We present TEMPLE, a domain specific language for modeling and solving staff scheduling problems. TEMPLE provides a set of intuitive abstractions and notations allowing to formulate the constraints of a particular problem in a very compact and natural way. After modeling a staff scheduling problem in TEMPLE, three generic local search algorithms can immediately be applied to the corresponding optimization problem. We show how real-life staff scheduling problems can be both effectively modeled as well as efficiently solved using our approach. Finally, we report on a practical application of TEMPLE in a commercial staff scheduling software.

2001

The typical process of planning and scheduling a rotating workforce in an organization consists in designing shifts and then assigning employees to these shifts and to periods of rest (days-off). Successfully solving these problems has high practical relevance: Results from ergonomics indicate that shift schedules have a profound impact on the health and satisfaction of employees as well as on their performance at work. The solutions must also satisfy legal requirements and should meet the objectives of the employing organization. In the research project Rota, undertaken by the Database and Artificial Intelligence Group at the Vienna University of Technology in cooperation with Ximes Corp., systems for the design of shifts and assignment of employees to shifts and days-off were developed. We give an overview of these systems.

This article presents a literature review of the current state of staff scheduling, in particular nurse scheduling. In current health care service, the critical problem in nurse scheduling in a hospital is how to determine day-to-day shift assignments of each nurse for a period of time in a way that satisfies the given requirements of a hospital. As a basis, the formal analysis of the problem is performed and a general scheduling procedure was established. Based on the method, a word processing template or software system which produces a scheduling program for a given institution was developed. Another objective of scheduling is optimization. Optimization of personnel scheduling consists of the selection of those work patterns that meet total work requirements at the lowest cost. Various approaches to alleviate the scheduling quagmire while attaining optimization are presented in this paper. Analysis of each of these approaches along with their effectiveness is presented. We anticipate that one of these approaches researched will provide the backbone to develop a system suitable for use at Duke University's medical oncology department.

An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 2020

In this study, a real assignment problem was discussed and the problem was considered as Generalized Assignment Problem. For the solution of the problem, related algorithms were listed and examined in the literature survey section. Then, a two-step method is proposed. First step prioritizes the task coming to the system by considering the customer types, service level agreement (SLA) times, cutoff times, task type. In the second step, a multi-objective mathematical model was developed to assign task to employee groups. A preference based optimization method called Linear Physical Programming (LPP) is used to solve the model. Afterward, proposed model was tested on real banking data. For all the tests, GAMS was used as a solver. Results show that proposed model gave better results compared with current situation. With the proposed solution method, the workloads of the profile groups working above their capacity were transferred to other profile groups with idle capacity. Thus, the capacity utilization rates of the profile groups were more balanced and the minimum capacity utilization rate was calculated as 41%.

European Journal of Operational Research, 2004

This paper presents a review of staff scheduling and rostering, an area that has become increasingly important as business becomes more service oriented and cost conscious in a global environment.Optimised staff schedules can provide enormous benefits, but require carefully implemented decision support systems if an organisation is to meet customer demands in a cost effective manner while satisfying requirements such as flexible workplace agreements, shift equity, staff preferences, and part-time work. In addition, each industry sector has its own set of issues and must be viewed in its own right. There are many computer software packages for staff scheduling, ranging from spreadsheet implementations of manual processes through to mathematical models using efficient optimal or heuristic algorithms. We do not review software packages in this paper. Rather, we review rostering problems in specific application areas, and the models and algorithms that have been reported in the literature for their solution. We also survey commonly used methods for solving rostering problems.

Brazilian Journal of Operations & …, 2010

In this paper we present a heuristic approach for solving workforce scheduling problems. The primary goal is to minimize the number of required workers given a pre-established shift demand over a planning horizon. The proposed algorithm starts with an initial solution (initial number of workers and their shift assignment) and iteratively searches the state space, moving towards better solutions via a local search procedure. Local optima are avoided by guaranteeing that the algorithm never returns to a previously visited solution. The algorithm stops after a termination criterion is met. The solution provides a detailed schedule of each worker on each shift. A number of constraints such as minimum and maximum number of working hours, rest days, and maximum number of continuous working hours are considered. The algorithm was tested on a number of randomly generated problems of different sizes. A Mixed Integer Programming (MIP) formulation is proposed and used as a benchmark. Computational experiments show that the algorithm always found optimal or near-optimal solutions with signifi cantly less computer effort.

Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l'Administration, 2018

This paper considers a case study of dynamic job scheduling applied to a real accounting operation. Tasks are assigned to agents over a time horizon minimizing the number of delays and overtime while maximizing the number of anticipated tasks. The solution respects a set of constraints such as agent skills, due time and precedence requirements. It also accounts for uncertainties by capturing changes in the environment such as new orders, changes in the agents' availability and unexpected problems while performing a task. The manager is given a chance to first simulate and then deploy corrective actions to mitigate the impact of changes in the environment. Two heuristics are developed and the results show a significant performance improvement in the operation.

Socio-Economic Planning Sciences, 1987

This paper proposes an interactive zero-one pre-emptive goal programming mode1 for real-world workforce scheduling procedures. To be useful in practice, the proposed mode1 takes into account the disaggregate and non-cyclical nature of staff scheduling decisions, which has been largely ignored in the existing literature. Hence, the model is partitioned into a number of smaller submodels based on three phases and then formulated for solving each separate and disaggregate level workforce scheduling problem. In addition, to make the mode1 computationally tractable for large-scale workforce scheduling problems, we propose and describe two efficient, and easy-to-use heuristics which even non-technical schedulers can implement. Finally, to demonstrate the practicality of the proposed model and its solution schemes, we present and discuss the application of the model to a real-world library s,taff scheduling decision.

This paper reports initial work done on the development of a framework for shift planning and scheduling in IT service operations management (ITSM). The framework includes effort and workforce (Full Time Equivalents) estimation, scheduling & shift planning and shift allocation. In order to accomplish this framework this paper considers 3 sets of data. Standard parameters for effort calculation, which includes available time for work as well as time spent on leaves and training per team member; application support window data; and data relating to application incident details. This paper succinctly describes a Java based application that implements this framework.