http://www3.eng.cam.ac.uk/~hj231/Papers/rostering.pdf

Staff scheduling and rostering: A review of applications, methods and models

Model-based analyses of natural selection often categorize sites into a relatively small number of site classes. Forcing each site to belong to one of these classes places unrealistic constraints on the distribution of selection parameters, which can result in misleading inference due to model misspecification. We present an approximate hierarchical Bayesian method using a Markov chain Monte Carlo (MCMC) routine that ensures robustness against model misspecification by averaging over a large number of predefined site classes. This leaves the distribution of selection parameters essentially unconstrained, and also allows sites experiencing positive and purifying selection to be identified orders of magnitude faster than by existing methods. We demonstrate that popular random effects likelihood methods can produce misleading results when sites assigned to the same site class experience different levels of positive or purifying selection—an unavoidable scenario when using a small number of site classes. Our Fast Unconstrained Bayesian AppRoximation (FUBAR) is unaffected by this problem, while achieving higher power than existing unconstrained (fixed effects likelihood) methods. The speed advantage of FUBAR allows us to analyze larger data sets than other methods: We illustrate this on a large influenza hemagglutinin data set (3,142 sequences). FUBAR is available as a batch file within the latest HyPhy distribution (http://www.hyphy.org), as well as on the Datamonkey web server (http://www.datamonkey.org/).

/pdf/fubar-a-fast-unconstrained-bayesian-approximation-for-1xo06i7bde.pdf

FUBAR : A Fast, Unconstrained Bayesian AppRoximation for inferring selection

https://web.stanford.edu/class/msande312/restricted/klos04facility.pdf

Facility location models for distribution system design

Nurse rostering is a complex scheduling problem that affects hospital personnel on a daily basis all over the world. The need for quality software solutions is acute for a number of reasons. In particular, it is very important to efficiently utilise time and effort, to evenly balance the workload among people and to attempt to satisfy personnel preferences. A high quality roster can lead to a more contented and thus more effective workforce.

In this review, we discuss nurse rostering within the global personnel scheduling problem in healthcare. We begin by briefly discussing the review and overview papers that have appeared in the literature and by noting the role that nurse rostering plays within the wider context of longer term hospital personnel planning. The main body of the paper describes and critically evaluates solution approaches which span the interdisciplinary spectrum from operations research techniques to artificial intelligence methods. We conclude by drawing on the strengths and weaknesses of the literature to outline the key issues that need addressing in future nurse rostering research.

/pdf/the-state-of-the-art-of-nurse-rostering-4uxzrvsub8.pdf

The State of the Art of Nurse Rostering

http://yoksis.bilkent.edu.tr/doi_getpdf/articles/10.1016-j.ejor.2007.06.008.pdf

Network hub location problems : The state of the art

Efficient algorithms for the uncapacitated single allocation p-hub median problem

Computational methods for rostering and personnel scheduling has been a subject of continued research and commercial interest since the 1950s. This annotated bibliography puts together a comprehensive collection of some 700 references in this area, focusing mainly on algorithms for generating rosters and personnel schedules but also covering related areas such as workforce planning and estimating staffing requirements. We classify these papers according to the type of problem addressed, the application areas covered and the methods used. In addition, a short summary is provided for each paper.

http://www3.eng.cam.ac.uk/~hj231/Papers/AORRosteringPaper.pdf

An Annotated Bibliography of Personnel Scheduling and Rostering

In this paper, we consider the problem of scheduling aircraft (plane) landings at an airport. This problem is one of deciding a landing time for each plane such that each plane lands within a predetermined time window and that separation criteria between the landing of a plane and the landing of all successive planes are respected. We present a mixed-integer zero--one formulation of the problem for the single runway case and extend it to the multiple runway case. We strengthen the linear programming relaxations of these formulations by introducing additional constraints. Throughout, we discuss how our formulations can be used to model a number of issues (choice of objective function, precedence restrictions, restricting the number of landings in a given time period, runway workload balancing) commonly encountered in practice. The problem is solved optimally using linear programming-based tree search. We also present an effective heuristic algorithm for the problem. Computational results for both the heuristic and the optimal algorithm are presented for a number of test problems involving up to 50 planes and four runways.

/pdf/scheduling-aircraft-landings-the-static-case-2va81e4kqb.pdf

Scheduling Aircraft Landings--The Static Case

In this paper, we present an efficient approach for solving capacitated single allocationhub location problems We use a modified version of a previous mixed integer linearprogramming formulation developed by us for p‐hub median problems This formulationrequires fewer variables and constraints than those traditionally used in the literature Wedevelop good heuristic algorithms for its solution based on simulated annealing (SA) andrandom descent (RDH) We use the upper bound to develop an LP‐based branch and boundsolution method The problem, as we define it, finds applications in the design of postaldelivery networks, particularly in the location of capacitated mail sorting and distributioncentres We test our algorithms on data obtained from this application To the best of ourknowledge, this problem has not been solved in the literature Computational results arepresented indicating the usefulness of our approach

Mohan Krishnamoorthy

Papers

Staff scheduling and rostering: A review of applications, methods and models

Efficient algorithms for the uncapacitated single allocation p-hub median problem

An Annotated Bibliography of Personnel Scheduling and Rostering

Scheduling Aircraft Landings--The Static Case

Solution algorithms for the capacitated single allocation hub location problem