Customer Focus Newsleter, January-February 2006, Vol. 3, no. 1

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsleter, March-April 2006, Vol. 3, no. 2

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsleter, July-August 2006, Vol. 3, no. 4

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsleter, September-October 2006, Vol. 3, no. 5

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsleter, November-December 2006, Vol. 3, no. 6

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsleter, Januart-February 2007, Vol. 4, no. 1

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsleter, March-April 2007, Vol. 4, no. 2

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsleter, May-June 2007, Vol. 4, no. 3

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsleter, July-August 2007, Vol. 4, no. 4

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsleter, November-December, 2007, Vol. 4, no. 6

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsleter, January/February, 2008, Vol. 5, no. 1

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

On certain greedoid polyhedra, partially indexable scheduling problems and extended restless bandit allocation indices

We present a polyhedral framework for establishing general structural properties on optimal solutions of stochastic scheduling problems, where multiple job classes vie for service resources: the existence of an optimal priority policy in a given family, characterized by a greedoid(whose feasible class subsets may receive higher priority), where optimal priorities are determined by class-ranking indices, under restricted linear performance objectives (partial indexability). This framework extends that of Bertsimas and Niño-Mora (1996), which explained the optimality of priority-index policies under all linear objectives (general indexability). We show that, if performance measures satisfy partial conservation laws (with respect to the greedoid), which extend previous generalized conservation laws, then theproblem admits a strong LP relaxation over a so-called extended greedoid polytope, which has strong structural and algorithmic properties. We present an adaptive-greedy algorithm (which extends Klimov's) taking as input the linear objective coefficients, which (1) determines whether the optimal LP solution is achievable by a policy in the given family; and (2) if so, computes a set of class-ranking indices that characterize optimal priority policies in the family. In the special case of project scheduling, we show that, under additional conditions, the optimal indices can be computed separately for each project (index decomposition). We further apply the framework to the important restless bandit model (two-action Markov decision chains), obtaining new index policies, that extend Whittle's (1988), and simple sufficient conditions for their validity. These results highlight the power of polyhedral methods (the so-called achievable region approach) in dynamic and stochastic optimization.

Customer Focus Newsletter, March/April, 2008, Vol. 5, no. 2

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

On the throughput-WIP trade-off in queueing systems, diminishing returns and the threshold property: A linear programming approach

We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.

Restless bandits, partial conservation laws and indexability

We show that if performance measures in a stochastic scheduling problem satisfy a set of so-called partial conservation laws (PCL), which extend previously studied generalized conservation laws (GCL), then the problem is solved optimally by a priority-index policy for an appropriate range of linear performance objectives, where the optimal indices are computed by a one-pass adaptive-greedy algorithm, based on Klimov's. We further apply this framework to investigate the indexability property of restless bandits introduced by Whittle, obtaining the following results: (1) we identify a class of restless bandits (PCL-indexable) which are indexable; membership in this class is tested through a single run of the adaptive-greedy algorithm, which also computes the Whittle indices when the test is positive; this provides a tractable sufficient condition for indexability; (2) we further indentify the class of GCL-indexable bandits, which includes classical bandits, having the property that they are indexable under any linear reward objective. The analysis is based on the so-called achievable region method, as the results follow fromnew linear programming formulations for the problems investigated.