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.

Abnormal cortical network activation in human amnesia: A high-resolution evoked potential study.

Little is known about how human amnesia affects the activation of cortical networks during memory processing. In this study, we recorded high-density evoked potentials in 12 healthy control subjects and 11 amnesic patients with various types of brain damage affecting the medial temporal lobes, diencephalic structures, or both. Subjects performed a continuous recognition task composed of meaningful designs. Using whole-scalp spatiotemporal mapping techniques, we found that, during the first 200 ms following picture presentation, map configuration of amnesics and controls were indistinguishable. Beyond this period, processing significantly differed. Between 200 and 350 ms, amnesic patients expressed different topographical maps than controls in response to new and repeated pictures. From 350 to 550 ms, healthy subjects showed modulation of the same maps in response to new and repeated items. In amnesics, by contrast, presentation of repeated items induced different maps, indicating distinct cortical processing of new and old information. The study indicates that cortical mechanisms underlying memory formation and re-activation in amnesia fundamentally differ from normal memory processing.

A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

A tractable consideration set structure for network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing from an offerset, have recently become popular in assortment optimization and revenue management. The dynamicprogram for these models is intractable and approximated by a deterministic linear program called theCDLP which has an exponential number of columns. When there are products that are being consideredfor purchase by more than one customer segment, CDLP is difficult to solve since column generationis known to be NP-hard. However, recent research indicates that a formulation based on segments withcuts imposing consistency (SDCP+) is tractable and approximates the CDLP value very closely. In thispaper we investigate the structure of the consideration sets that make the two formulations exactly equal.We show that if the segment consideration sets follow a tree structure, CDLP = SDCP+. We give acounterexample to show that cycles can induce a gap between the CDLP and the SDCP+ relaxation.We derive two classes of valid inequalities called flow and synchronization inequalities to further improve(SDCP+), based on cycles in the consideration set structure. We give a numeric study showing theperformance of these cycle-based cuts.

Diabetes mellitus and cancer risk in a network of case-control studies.

Diabetes has been associated to the risk of a few cancer sites, though quantification of this association in various populations remains open to discussion. We analyzed the relation between diabetes and the risk of various cancers in an integrated series of case-control studies conducted in Italy and Switzerland between 1991 and 2009. The studies included 1,468 oral and pharyngeal, 505 esophageal, 230 gastric, 2,390 colorectal, 185 liver, 326 pancreatic, 852 laryngeal, 3,034 breast, 607 endometrial, 1,031 ovarian, 1,294 prostate, and 767 renal cell cancer cases and 12,060 hospital controls. The multivariate odds ratios (OR) for subjects with diabetes as compared to those without-adjusted for major identified confounding factors for the cancers considered through logistic regression models-were significantly elevated for cancers of the oral cavity/pharynx (OR = 1.58), esophagus (OR = 2.52), colorectum (OR = 1.23), liver (OR = 3.52), pancreas (OR = 3.32), postmenopausal breast (OR = 1.76), and endometrium (OR = 1.70). For cancers of the oral cavity, esophagus, colorectum, liver, and postmenopausal breast, the excess risk persisted over 10 yr since diagnosis of diabetes. Our data confirm and further quantify the association of diabetes with colorectal, liver, pancreatic, postmenopausal breast, and endometrial cancer and suggest forthe first time that diabetes may also increase the risk of oral/pharyngeal and esophageal cancer. [Table: see text] [Table: see text].

Equivalence of piecewise-linear approximation and Lagrangian relaxation for network revenue management

The network revenue management (RM) problem arises in airline, hotel, media,and other industries where the sale products use multiple resources. It can be formulatedas a stochastic dynamic program but the dynamic program is computationallyintractable because of an exponentially large state space, and a number of heuristicshave been proposed to approximate it. Notable amongst these -both for their revenueperformance, as well as their theoretically sound basis- are approximate dynamic programmingmethods that approximate the value function by basis functions (both affinefunctions as well as piecewise-linear functions have been proposed for network RM)and decomposition methods that relax the constraints of the dynamic program to solvesimpler dynamic programs (such as the Lagrangian relaxation methods). In this paperwe show that these two seemingly distinct approaches coincide for the network RMdynamic program, i.e., the piecewise-linear approximation method and the Lagrangianrelaxation method are one and the same.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.

Quetiapine affects neuropeptide Y and corticotropin-releasing hormone in cerebrospinal fluid from schizophrenia patients: relationship to depression and anxiety symptoms and to treatment response.

Cumulative evidence indicates that neuropeptides play a role in the pathophysiology of schizophrenia. Early data showed increased neuropeptide Y (NPY) in cerebrospinal fluid (CSF) from schizophrenia patients and data from rodents show that antipsychotic drugs modulate NPY levels in and release from selected rat brain regions. In view of these findings we investigated whether the atypical antipsychotic quetiapine, originally used as an antipsychotic but subsequently shown to be efficient also in major depressive disorder and in both poles of bipolar disorder, would affect NPY-like immunoreactivity (-LI), and corticotropin-releasing hormone (CRH)-LI levels in CSF of schizophrenia patients. NPY-LI and CRH-LI in CSF were determined in 22 patients with schizophrenia. Lumbar puncture was performed at baseline and again after 4 wk of quetiapine treatment (600 mg/d). Patients were assessed with the Positive and Negative Syndrome Scale (PANSS) at baseline and at weekly intervals. Quetiapine treatment was associated with a significant increase in NPY-LI (p<0.001) and decrease in CRH-LI (p<0.01). Stepwise multiple regression analysis revealed that ΔNPY-LI and ΔCRH-LI levels predicted 63% (p<0.001) of the variability of the ΔPANSS total score, ΔNPY-LI 42% (p<0.05) of the ΔPANSS anxiety items (G2) and ΔCRH-LI 40% (p=0.05) of the ΔPANSS depression items (G6). These results suggest that while quetiapine's effects on monoamines are probably related to its antipsychotic properties, the modulation of NPY and CRH accounts for its antidepressant and anxiolytic effects and can be markers of response.

The dynamics of research networks in Brite-Euram

Network formation within the BRITE--EURAM program is investigated.Wedescribe the role of the hub of the network, which is defined as the setofmain contractors that account for most of the participations. We studytheeffects that the conflict of objectives within European research fundingbetween pre-competitive research vs. European cohesion has on theformationof networks and on the relationship between different partnersof the network. \\A panel data set is constructed including the second and third frameworkof theBrite--Euram program. A model of joint production of research results isusedto test for changes in the behavior of partners within the twoframeworks. \\The main findings are that participations are very concentrated, that isasmall group of institutions account for most of the participations, butgoingfrom the second to the third framework the presence of subcontractorsand singleparticipants increases substantially. This result is reinforced by the factthat main contractors receive smaller spill-ins within networks, butspill-insincrease from the second to the third framework.

Aggregate fluctuations and the network structure of intersectoral trade

This paper analyzes the flow of intermediate inputs across sectors by adopting a network perspective on sectoral interactions. I apply these tools to show how fluctuationsin aggregate economic activity can be obtained from independent shocks to individualsectors. First, I characterize the network structure of input trade in the U.S. On thedemand side, a typical sector relies on a small number of key inputs and sectors arehomogeneous in this respect. However, in their role as input-suppliers sectors do differ:many specialized input suppliers coexist alongside general purpose sectors functioningas hubs to the economy. I then develop a model of intersectoral linkages that can reproduce these connectivity features. In a standard multisector setup, I use this modelto provide analytical expressions linking aggregate volatility to the network structureof input trade. I show that the presence of sectoral hubs - by coupling productiondecisions across sectors - leads to fluctuations in aggregates.

An ASsessment of Relationship between Students' Perception of Social Studies and their Academic Performance in Colleges of Education in Kaduna State

The objective of this study was to find out the relationship between students’ perception of Social Studies and their academic performance in the subject in Colleges of Education in Kaduna State. The respondents of the study comprised NCE 2 and NCE 3 students of Social Studies at the Federal College of Education in Zaria and the Kaduna State College of Education in Gidan Waya. The data for the study was collected using a questionnaire with reliability coefficient of 0.87. The Pearson’s Product Moment Correlation Coefficient was used to test the hypotheses formulated for the study. The hypotheses were tested at 0.05 level of significance with df = 232. The findings were as follows: 1. The Social Studies students in colleges of education in Kaduna State do not record high academic performance in the subject. 2. Students’ perception of the Social Studies curriculum does affect their academic performance in the subject 3. Students’ perception of relevance of Social Studies education has no bearing on their academic performance in the subject. 4. Students’ perception of public attitude towards Social Studies has no impact on their academic performance in the subject. 5. Students’ general perception of Social Studies does not affect their academic performance in the subject. Based on these findings the following recommendations were proffered for Social Studies researchers and policy makers. a. There is need for further research in order to determine the actual cause of students’ failure to display high performance in Social Studies. b. The NCE Social Studies curriculum should be reviewed in terms of volume and difficulty.