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 the problem 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.

Optimal Contracts, Adverse Selection, and Social Preferences: An Experiment

It has long been standard in agency theory to search for incentive-compatible mechanisms on the assumption that people care only about their own material wealth. However, this assumption is clearly refuted by numerous experiments, and we feel that it may be useful to consider nonpecuniary utility in mechanism design and contract theory. Accordingly, we devise an experiment to explore optimal contracts in an adverse-selection context. A principal proposes one of three contract menus, each of which offers a choice of two incentive-compatible contracts, to two agents whose types are unknown to the principal. The agents know the set of possible menus, and choose to either accept one of the two contracts offered in the proposed menu or to reject the menu altogether; a rejection by either agent leads to lower (and equal) reservation payoffs for all parties. While all three possible menus favor the principal, they do so to varying degrees. We observe numerous rejections of the more lopsided menus, and approach an equilibrium where one of the more equitable contract menus (which one depends on the reservation payoffs) is proposed and agents accept a contract, selecting actions according to their types. Behavior is largely consistent with all recent models of social preferences, strongly suggesting there is value in considering nonpecuniary utility in agency theory.

Optimal Design of Permit Markets with an Ex Ante Pollution Target, August 2006

In this paper, we examine the design of permit trading programs when the objective is to minimize the cost of achieving an ex ante pollution target, that is, one that is defined in expectation rather than an ex post deterministic value. We consider two potential sources of uncertainty, the presence of either of which can make our model appropriate: incomplete information on abatement costs and uncertain delivery coefficients. In such a setting, we find three distinct features that depart from the well-established results on permit trading: (1) the regulator’s information on firms’ abatement costs can matter; (2) the optimal permit cap is not necessarily equal to the ex ante pollution target; and (3) the optimal trading ratio is not necessarily equal to the delivery coefficient even when it is known with certainty. Intuitively, since the regulator is only required to meet a pollution target on average, she can set the trading ratio and total permit cap such that there will be more pollution when abatement costs are high and less pollution when abatement costs are low. Information on firms’ abatement costs is important in order for the regulator to induce the optimal alignment between pollution level and abatement costs.

A Simple Access Pricing Rule to Achieve the Ramsey Outcome in Two-Way Access

In this paper, I consider a general and informationally effcient approach to determine the optimal access rule and show that there exists a simple rule that achieves the Ramsey outcome as the unique equilibrium when networks compete in linear prices without network-based price discrimination. My approach is informationally effcient in the sense that the regulator is required to know only the marginal cost structure, i.e. the marginal cost of making and terminating a call. The approach is general in that access prices can depend not only on the marginal costs but also on the retail prices, which can be observed by consumers and therefore by the regulator as well. In particular, I consider the set of linear access pricing rules which includes any fixed access price, the Efficient Component Pricing Rule (ECPR) and the Modified ECPR as special cases. I show that in this set, there is a unique access rule that achieves the Ramsey outcome as the unique equilibrium as long as there exists at least a mild degree of substitutability among networks' services.

Compétences en santé déficientes: obstacle à une prise en charge optimale [Low health literacy: barrier to optimal care].

Health literacy is defined as "the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions." Low health literacy mainly affects certain populations at risk limiting access to care, interaction with caregivers and self-management. If there are screening tests, their routine use is not advisable and recommended interventions in practice consist rather to reduce barriers to patient-caregiver communication. It is thus important to include not only population's health literacy but also communication skills of a health system wich tend to become more complex.

Partitioning of reproduction in mother-daughter versus sibling associations : a test of optimal skew theory

A critical feature of cooperative animal societies is the reproductive skew, a shorthand term for the degree to which a dominant individual monopolizes overall reproduction in the group. Our theoretical analysis of the evolutionarily stable skew in matrifilial (i.e., mother-daughter) societies, in which relatednesses to offspring are asymmetrical, predicts that reproductive skews in such societies should tend to be greater than those of semisocial societies (i.e., societies composed of individuals of the same generation, such as siblings), in which relatednesses to offspring are symmetrical. Quantitative data on reproductive skews in semisocial and matrifilial associations within the same species for 17 eusocial Hymenoptera support this prediction. Likewise, a survey of reproductive partitioning within 20 vertebrate societies demonstrates that complete reproductive monopoly is more likely to occur in matrifilial than in semisocial societies, also as predicted by the optimal skew model.

Combined transesophageal and surface MRI provides optimal imaging in aortic atherosclerosis.

OBJECTIVE: Surface magnetic resonance imaging (MRI) for aortic plaque assessment is limited by the trade-off between penetration depth and signal-to-noise ratio (SNR). For imaging the deep seated aorta, a combined surface and transesophageal MRI (TEMRI) technique was developed 1) to determine the individual contribution of TEMRI and surface coils to the combined signal, 2) to measure the signal improvement of a combined surface and TEMRI over surface MRI, and 3) to assess for reproducibility of plaque dimension analysis. METHODS AND RESULTS: In 24 patients six black blood proton-density/T2-weighted fast-spin echo images were obtained using three surface and one TEMRI coil for SNR measurements. Reproducibility of plaque dimensions (combined surface and TEMRI) was measured in 10 patients. TEMRI contributed 68% of the signal in the aortic arch and descending aorta, whereas the overall signal gain using the combined technique was up to 225%. Plaque volume measurements had an intraclass correlation coefficient of as high as 0.97. CONCLUSION: Plaque volume measurements for the quantification of aortic plaque size are highly reproducible for combined surface and TEMRI. The TEMRI coil contributes considerably to the aortic MR signal. The combined surface and TEMRI approach improves aortic signal significantly as compared to surface coils alone. CONDENSED ABSTRACT: Conventional MRI aortic plaque visualization is limited by the penetration depth of MRI surface coils and may lead to suboptimal image quality with insufficient reproducibility. By combining a transesophageal MRI (TEMRI) with surface MRI coils we enhanced local and overall image SNR for improved image quality and reproducibility.

Importância da Programação Linear na Determinação de Informações de Gestão - Caso Moave, Sa

A Investigação Operacional vem demonstrando ser uma valiosa ferramenta de gestão nos dias de hoje em que se vive num mercado cada vez mais competitivo. Através da Programação Linear pode-se reproduzir matematicamente um problema de maximização dos resultados ou minimização dos custos de produção com o propósito de auxiliar os gestores na tomada de decisão. A Programação Linear é um método matemático em que a função objectivo e as restrições assumem características lineares, com diversas aplicações no controlo de gestão, envolvendo normalmente problemas de utilização dos recursos disponíveis sujeitos a limitações impostas pelo processo produtivo ou pelo mercado. O objectivo geral deste trabalho é o de propor um modelo de Programação Linear para a programação ou produção e alocação de recursos necessários. Optimizar uma quantidade física designada função objectivo, tendo em conta um conjunto de condicionalismos endógenas às actividades em gestão. O objectivo crucial é dispor um modelo de apoio à gestão contribuindo assim para afectação eficiente de recursos escassos à disposição da unidade económica. Com o trabalho desenvolvido ficou patente a importância da abordagem quantitativa como recurso imprescindível de apoio ao processo de decisão. The operational research has proven to be a valuable management tool today we live in an increasingly competitive market. Through Linear Programming can be mathematically reproduce a problem of maximizing performance or minimizing production costs in order to assist managers in decision making. The Linear Programming is a mathematical method in which the objective function and constraints are linear features, with several applications in the control of management, usually involving problems of resource use are available subject to limitations imposed by the production process or the market. The overall objective of this work is to propose a Linear Programming model for scheduling or production and allocation of necessary resources. Optimizing a physical quantity called the objective function, given a set of endogenous constraints on management thus contributing to efficient allocation of scarce resources available to the economic unit. With the work has demonstrated the importance of the quantitative approach as essential resource to support the decision process.

A theory of optimal random crackdowns

An incentives based theory of policing is developed which can explain the phenomenon of random “crackdowns,” i.e., intermittent periods of high interdiction/surveillance. For a variety of police objective functions, random crackdowns can be part of the optimal monitoring strategy. We demonstrate support for implications of the crackdown theory using traffic data gathered by the Belgian Police Department and use the model to estimate the deterrence effectof additional resources spent on speeding interdiction.

Enhanced generation of specific tumor-reactive CTL in vitro by selected Melan-A/MART-1 immunodominant peptide analogues.

The Melan-A/MART-1 gene, which is expressed by normal melanocytes as well as by most fresh melanoma samples and melanoma cell lines, codes for Ags recognized by tumor-reactive CTL. HLA-A*0201-restricted Melan-A-specific CTL recognize primarily the Melan-A(27-35) (AAGIGILTV) and the Melan-A(26-35) (EAAGIGILTV) peptides. The sequences of these two peptides are not necessarily optimal as far as binding to HLA-A*0201 is concerned, since both lack one of the dominant anchor amino acid residues (leucine or methionine) at position 2. In this study we introduced single amino acid substitutions in either one of the two natural peptide sequences with the aim of improving peptide binding to HLA-A*0201 and/or recognition by specific CTL. Surprisingly, analogues of the Melan-A(27-35) peptide, which bound more efficiently than the natural nonapeptide to HLA-A*0201, were poorly recognized by tumor-reactive CTL. In contrast, among the Melan-A(26-35) peptide analogues tested, the peptide ELAGIGILTV was not only able to display stable binding to HLA-A2.1 but was also recognized more efficiently than the natural peptide by two short-term cultured tumor-infiltrated lymph node cell cultures as well as by five of five tumor-reactive CTL clones. Moreover, in vitro generation of tumor-reactive CTL by stimulation of PBMC from HLA-A*0201 melanoma patients with this particular peptide analogue was much more efficient than that observed with either one of the two natural peptides. These results suggest that the Melan-A(26-35) peptide analogue ELAGIGILTV may be more immunogenic than the natural peptides in HLA-A*0201 melanoma patients and should thus be considered as a candidate for future peptide-based vaccine trials.

On optimal monetary and fiscal policy interactions in open economies

This paper studies monetary and fiscal policy interactions in a two country model, where taxes on firms sales are optimally chosen and the monetary policy is set cooperatively.It turns out that in a two country setting non-cooperative fiscal policy makers have an incentive to change taxes on sales depending on shocks realizations in order to reduce output production. Therefore whether the fiscal policy is set cooperatively or not matters for optimal monetary policy decisions. Indeed, as already shown in the literature, the cooperative monetary policy maker implements the flexible price allocation only when special conditions on the value of the distortions underlying the economy are met. However, if non-cooperative fiscal policy makers set the taxes on firms sales depending on shocks realizations, these conditions cannot be satisfied; conversely, when fiscal policy is cooperative, these conditions are fulfilled. We conclude that whether implementing the flexible price allocation is optimal or not depends on the fiscal policy regime.

Determinants of linear judgment: A meta-analysis of lens model studies

The mathematical representation of Brunswik s lens model has been usedextensively to study human judgment and provides a unique opportunity to conduct ameta-analysis of studies that covers roughly five decades. Specifically, we analyzestatistics of the lens model equation (Tucker, 1964) associated with 259 different taskenvironments obtained from 78 papers. In short, we find on average fairly high levelsof judgmental achievement and note that people can achieve similar levels of cognitiveperformance in both noisy and predictable environments. Although overall performancevaries little between laboratory and field studies, both differ in terms of components ofperformance and types of environments (numbers of cues and redundancy). An analysisof learning studies reveals that the most effective form of feedback is information aboutthe task. We also analyze empirically when bootstrapping is more likely to occur. Weconclude by indicating shortcomings of the kinds of studies conducted to date, limitationsin the lens model methodology, and possibilities for future research.

Network revenue management with product-specific no-shows

Revenue management practices often include overbooking capacity to account for customerswho make reservations but do not show up. In this paper, we consider the network revenuemanagement problem with no-shows and overbooking, where the show-up probabilities are specificto each product. No-show rates differ significantly by product (for instance, each itinerary andfare combination for an airline) as sale restrictions and the demand characteristics vary byproduct. However, models that consider no-show rates by each individual product are difficultto handle as the state-space in dynamic programming formulations (or the variable space inapproximations) increases significantly. In this paper, we propose a randomized linear program tojointly make the capacity control and overbooking decisions with product-specific no-shows. Weestablish that our formulation gives an upper bound on the optimal expected total profit andour upper bound is tighter than a deterministic linear programming upper bound that appearsin the existing literature. Furthermore, we show that our upper bound is asymptotically tightin a regime where the leg capacities and the expected demand is scaled linearly with the samerate. We also describe how the randomized linear program can be used to obtain a bid price controlpolicy. Computational experiments indicate that our approach is quite fast, able to scale to industrialproblems and can provide significant improvements over standard benchmarks.