A Capacity Allocation Planning Model for Integrated Care and Access Management

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146954/1/poms12941-sup-0001-AppendixS1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146954/2/poms12941_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146954/3/poms12941.pd

On the Introduction of an Agile, Temporary Workforce into a Tandem Queueing System

We consider a two-station tandem queueing system where customers arrive according to a Poisson process and must receive service at both stations before leaving the system. Neither queue is equipped with dedicated servers. Instead, we consider three scenarios for the fluctuations of workforce level. In the first, a decision-maker can increase and decrease the capacity as is deemed appropriate; the unrestricted case. In the other two cases, workers arrive randomly and can be rejected or allocated to either station. In one case the number of workers can then be reduced (the controlled capacity reduction case). In the other they leave randomly (the uncontrolled capacity reduction case). All servers are capable of working collaboratively on a single job and can work at either station as long as they remain in the system. We show in each scenario that all workers should be allocated to one queue or the other (never split between queues) and that they should serve exhaustively at one of the queues depending on the direction of an inequality. This extends previous studies on flexible systems to the case where the capacity varies over time. We then show in the unrestricted case that the optimal number of workers to have in the system is non-decreasing in the number of customers in either queue.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47647/1/11134_2005_Article_2441.pd

Agile Workforce Evaluation: A Framework for Cross-training and Coordination

This paper outlines frameworks for assessing and classifying manufacturing and service operations in terms of their suitability for use of cross-trained (flexible) workers. We refer to our combined framework as Agile Workforce Evaluation (AWE). The primary contributions of this paper are: (1) a strategic assessment framework that structures the key mechanisms by which cross-training can support organizational strategy, (2) a tactical framework that identifies key factors to guide the selection of an architecture and worker coordination policy for implementing workforce agility, (3) a classification of workforce agility architectures, (4) a survey of a broad range of archetypical classes of worker coordination policies, (5) a survey of the literature with an operational perspective on workforce agility set within our frameworks, and (6) the identification of opportunities for research and development of architectures for specific production environments

Optimal Stochastic Scheduling of Forest Network with Switching Penalties,’ mimeo

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available a

Heuristic Scheduling of Parallel Heterogeneous Queues with Set-Ups

We consider the problem of allocating a single server to a system of queues with Poisson arrivals. Each queue represents a class of jobs and possesses a holding cost rate, general service distribution, and general set-up time distribution. The objective is to minimize the expected holding cost due to the waiting of jobs. A set-up time is required to switch from one queue to another. We provide a limited characterization of the optimal policy and a simple heuristic scheduling policy for this problem. Simulation results demonstrate the effectiveness of our heuristic over a wide range of problem instances