Provably Near-Optimal LP-Based Policies for Revenue Management in Systems with Reusable Resources

Motivated by emerging applications in workforce management, we consider a class of revenue management problems in systems with reusable resources. The corresponding applications are modeled using the well-known loss network systems. We use an extremely simple linear program (LP) that provides an upper bound on the best achievable expected long-run revenue rate. The optimal solution of the LP is used to devise a conceptually simple control policy that we call the class selection policy (CSP). Moreover, the LP is used to analyze the performance of the CSP policy. We obtain the _rst control policy with uniform performance guarantees. In particular, for the model with single resource and uniform resource requirements, the CSP policy is guaranteed to have expected long-run revenue rate that is at least half of the best achievable. More generally, as the ratio between the capacity of the system and the maximum resource requirement grows to in_nity, the CSP policy is asymptotically optimal, regardless of any other parameter of the problem. The asymptotic performance analysis that we obtain is more general than existing results in several important dimensions. It is based on several novel ideas that we believe will be useful in other settings

Revenue Management of Reusable Resources with Advanced Reservations

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137568/1/poms12672_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137568/2/poms12672.pd

Dynamic bandwidth allocation in multi-class IP networks using utility functions.

PhDAbstact not availableFujitsu Telecommunications Europe Lt

Switching techniques for broadband ISDN

The properties of switching techniques suitable for use in broadband networks have been investigated. Methods for evaluating the performance of such switches have been reviewed. A notation has been introduced to describe a class of binary self-routing networks. Hence a technique has been developed for determining the nature of the equivalence between two networks drawn from this class. The necessary and sufficient condition for two packets not to collide in a binary self-routing network has been obtained. This has been used to prove the non-blocking property of the Batcher-banyan switch. A condition for a three-stage network with channel grouping and link speed-up to be nonblocking has been obtained, of which previous conditions are special cases. A new three-stage switch architecture has been proposed, based upon a novel cell-level algorithm for path allocation in the intermediate stage of the switch. The algorithm is suited to hardware implementation using parallelism to achieve a very short execution time. An array of processors is required to implement the algorithm The processor has been shown to be of simple design. It must be initialised with a count representing the number of cells requesting a given output module. A fast method has been described for performing the request counting using a non-blocking binary self-routing network. Hardware is also required to forward routing tags from the processors to the appropriate data cells, when they have been allocated a path through the intermediate stage. A method of distributing these routing tags by means of a non-blocking copy network has been presented. The performance of the new path allocation algorithm has been determined by simulation. The rate of cell loss can increase substantially in a three-stage switch when the output modules are non-uniformly loaded. It has been shown that the appropriate use of channel grouping in the intermediate stage of the switch can reduce the effect of non-uniform loading on performance

Hierarchical Multiobjective Routing in MPLS Networks with Two Service Classes – A Meta-Heuristic Solution, Journal of Telecommunications and Information Technology, 2009, nr 3

The paper begins by reviewing a two-level hierarchical multicriteria routing model for MPLS networks with two service classes (QoS and BE services) and alternative routing, as well as the foundations of a heuristic resolution approach, previously proposed by the authors. Afterwards a new approach, of meta-heuristic nature, based on the introduction of simulated annealing and tabu search techniques, in the structure of the dedicated heuristic, is described. The application of the developed procedures to a benchmarking case study will show that, in certain initial conditions, this approach provides improvements in the final results especially in more “difficult” situations detected through sensitivity analysis

Provably near-optimal algorithms for multi-stage stochastic optimization models in operations management

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 157-165).Many if not most of the core problems studied in operations management fall into the category of multi-stage stochastic optimization models, whereby one considers multiple, often correlated decisions to optimize a particular objective function under uncertainty on the system evolution over the future horizon. Unfortunately, computing the optimal policies is usually computationally intractable due to curse of dimensionality. This thesis is focused on providing provably near-optimal and tractable policies for some of these challenging models arising in the context of inventory control, capacity planning and revenue management; specifically, on the design of approximation algorithms that admit worst-case performance guarantees. In the first chapter, we develop new algorithmic approaches to compute provably near-optimal policies for multi-period stochastic lot-sizing inventory models with positive lead times, general demand distributions and dynamic forecast updates. The proposed policies have worst-case performance guarantees of 3 and typically perform very close to optimal in extensive computational experiments. We also describe a 6-approximation algorithm for the counterpart model under uniform capacity constraints. In the second chapter, we study a class of revenue management problems in systems with reusable resources and advanced reservations. A simple control policy called the class selection policy (CSP) is proposed based on solving a knapsack-type linear program (LP). We show that the CSP and its variants perform provably near-optimal in the Halfin- Whitt regime. The analysis is based on modeling the problem as loss network systems with advanced reservations. In particular, asymptotic upper bounds on the blocking probabilities are derived. In the third chapter, we examine the problem of capacity planning in joint ventures to meet stochastic demand in a newsvendor-type setting. When resources are heterogeneous, there exists a unique revenue-sharing contract such that the corresponding Nash Bargaining Solution, the Strong Nash Equilibrium, and the system optimal solution coincide. The optimal scheme rewards every participant proportionally to her marginal cost. When resources are homogeneous, there does not exist a revenue-sharing scheme which induces the system optimum. Nonetheless, we propose provably good revenue-sharing contracts which suggests that the reward should be inversely proportional to the marginal cost of each participant.by Cong Shi.Ph.D