An Algorithmic approach to shift structure optimization

Workforce scheduling in organizations often consists of three major phases: workload prediction, shift generation, and staff rostering. Workload prediction involves using historical behaviour of e.g. customers to predict future demand for work. Shift generation is the process of transforming the determined workload into shifts as accurately as possible. In staff rostering, the generated shifts are assigned to employees. In general the problem and even its subproblems are NP-hard, which makes them highly challenging for organizations to solve. Heuristic optimization methods can be used to solve practical instances within reasonable running times, which in turn can result in e.g. improved revenue, improved service, or more satisfied employees for the organizations. This thesis presents some specific subproblems along with practical solution methods--- Työvoiman aikataulutusprosessi koostuu kolmesta päävaiheesta: työtarpeen ennustaminen, työvuorojen muodostus ja työvuorojen miehitys. Tulevaa työtarvetta ennustetaan pääasiassa menneisyyden asiakaskäytöksen perusteella käyttäen esimerkiksi tilastollisia malleja tai koneoppimiseen perustuvia menetelmiä. Työvuorojen muodostuksessa tehdään työvuororakenne, joka noudattaa ennustettua ja ennalta tiedettyä työtarvetta mahdollisimman tarkasti. Työvuorojen miehityksessä määritetään työvuoroille tekijät. Jokainen vaihe itsessään on haasteellinen ratkaistava. Erityisesti työvuorojen miehitys on yleensä NP-kova ongelma. On kuitenkin mahdollista tuottaa käytännöllisiä ratkaisuja järkevässä ajassa käyttäen heuristisia optimointimenetelmiä. Näin on saavutettavissa mitattavia hyötyjä mm. tuottoon, asiakkaiden palvelutasoon sekä työntekijöiden työtyyväisyyteen. Tässä väitöskirjassa esitellään eräitä työvoiman aikataulutuksen aliongelmia sekä niihin sopivia ratkaisumenetelmiä

Improving the Utilization of Front-Line Service Delivery System Personnel

There are two types of work typically performed in services which differ in the degree of control management has over when the work must be done. Serving customers, an activity that can occur only when customers are in the system is, by its nature, uncontrollable work. In contrast, the execution of controllable work does not require the presence of customers, and is work over which management has some degree of temporal control. This paper presents two integer programming models for optimally scheduling controllable work simultaneously with shifts. One model explicitly defines variables for the times at which controllable work may be started, while the other uses implicit modeling to reduce the number of variables. In an initial experiment of 864 test problems, the latter model yielded optimal solutions in approximately 81 percent of the time required by the former model. To evaluate the impact on customer service of having front-line employees perform controllable work, a second experiment was conducted simulating 5,832 service delivery systems. The results show that controllable work offers a useful means of improving labor utilization. Perhaps more important, it was found that having front-line employees perform controllable work did not degrade the desired level of customer service

Proactive and reactive strategies for resource-constrained project scheduling with uncertain resource availabilities.

Research concerning project planning under uncertainty has primarily focused on the stochastic resource-constrained project scheduling problem (stochastic RCPSP), an extension of the basic CPSP, in which the assumption of deterministic activity durations is dropped. In this paper, we introduce a new variant of the RCPSP for which the uncertainty is modeled by means of resource availabilities that are subject to unforeseen breakdowns. Our objective is to build a robust schedule that meets the project due date and minimizes the schedule instability cost, defined as the expected weighted sum of the absolute deviations between the planned and actually realized activity starting times during project execution. We describe how stochastic resource breakdowns can be modeled, which reaction is recommended when are source infeasibility occurs due to a breakdown and how one can protect the initial schedule from the adverse effects of potential breakdowns.

Coherent Dynamics of Vortex Formation in Trapped Bose-Einstein Condensates

Simulations of a rotationally stirred condensate show that a regime of simple behaviour occurs in which a single vortex cycles in and out of the condensate. We present a simple quantitative model of this behaviour, which accurately describes the full vortex dynamics, including a critical angular speed of stirring for vortex formation. A method for experimentally preparing a condensate in a central vortex state is suggested.Comment: 4 pages, 4 figures, REVTeX 3.1; Submitted to Physical Review Letters (5 February 1999); See http://www.physics.otago.ac.nz/research/bec/vortex for MPEG movies and further information; Accepted for Physical Review Letters (24 June 1999); Changes: updated Figs 1 and 2 (new style), minor typos fixed, more discussion at en

A survey on constructing rosters for air traffic controllers

In this survey the state-of-the-art technology and the literature to date are discussed. In particular, we will discuss the gap in the literature concerning rostering staff to tasks by qualifications, with the inclusion of restrictions on a measure of task familiarity, which is a unique consequence of the structure of ATC operations

Railway Crew Rescheduling with Retiming

Railway operations are disrupted frequently, e.g. the Dutch railway network experiences about three large disruptions per day on average. In such a disrupted situation railway operators need to quickly adjust their resource schedules. Nowadays, the timetable, the rolling stock and the crew schedule are recovered in a sequential way. In this paper, we model and solve the crew rescheduling problem with retiming. This problem extends the crew rescheduling problem by the possibility to delay the departure of some trains. In this way we partly integrate timetable adjustment and crew rescheduling. The algorithm is based on column generation techniques combined with Lagrangian heuristics. In order to prevent a large increase in computational time, retiming is allowed only for a limited number of trains where it seems very promising. Computational experiments with real-life disruption data show that, compared to the classical approach, it is possible to find better solutions by using crew rescheduling with retiming.

Design of an Automated Employee Scheduling System

Many retail stores, as well as other organizations that employ a multitude of part-time employees, rely on developing schedules frequently, since the availabilities of the employees as well as the needs of the business change often. This process is often performed on a weekly basis, and is complex and time-consuming. The schedule must typically satisfy numerous requirements, including business needs, legal restrictions, and employee availability constraints. As a result, errors are common, and employee time that could have been spent on improving sales or operations is instead consumed by the scheduling task. This project explores two solution methods for this problem. One method is the use of linear programming (LP) to develop an optimal schedule weekly. The other is the design and implementation of a scheduling system that uses a heuristic method. After developing both methods it was determined that while the LP approach may lead to optimal solutions, it was impractical due to high costs and complexity. The heuristic approach resulted in an automatic scheduling system that is easy to use, low cost, and flexible. The new scheduling system was evaluated and approved by future users