Department of Computer Science & Engineering

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Flexibility in curriculum, in all its academic programs, encompassing elements of teaching, research, creativity, innovation and entrepreneurship is the most unique feature of IIT Jodhpur. The Department of Science and Technology (DST), under the National Mission on Cyber Physical Systems, has identified IIT Jodhpur as a Technology &amp; Innovation Hub in the area of Augmented Reality and Virtual Reality. The institute has also been nominated as the coordinator for the Jodhpur City and Knowledge Cluster by the Office of Principal Scientific Adviser, Government of India.

The sprawling 852-acre IIT Jodhpur campus is a majestic tribute to the deep-rooted diverse cultural heritage of the region. The campus is an architectural masterpiece, which is slated to become an international exemplar of sustainability with net-zero energy, and advanced water and waste management strategies.&rdquo;

IIT Jodhpur

School of Artificial Intelligence and Data Science (AIDE)

Geoffrion proper optimality is a widely used optimality notion in multicriteria optimization that prevents exact solutions having unbounded trade-offs. As algorithms for multicriteria optimization usually give only approximate solutions, we analyze the notion of approximate Geoffrion proper optimality. We show that in the limit, approximate Geoffrion proper optimality may converge to solutions having unbounded trade-offs. Therefore, we introduce a restricted notion of approximate Geoffrion proper optimality and prove that this restricted notion alleviates the problem of solutions having unbounded trade-offs. Furthermore, using a characterization based on the infeasibility of a system of inequalities, we investigate the convergence properties of different approximate optimality notions in multicriteria optimization. These convergence properties are important for algorithmic reasons. The restricted notion of approximate Geoffrion proper optimality seems to be the only approximate optimality notion that shows favourable convergence properties. This notion bounds the trade-offs globally and can be used in multicriteria decision-making algorithms as well. Due to these, it seems to be a practical optimality notion. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

World University root node

Optimization

On a practical notion of Geoffrion proper optimality in multicriteria optimization

The role of two policy pillars in achieving immunisation coverage of essential vaccines in India is examined by assessing the funds disbursed by the centre to the state governments under the Universal Immunisation Programme and the available physical health infrastructure in the states. It is found that funds by themselves are ineffective in improving vaccination coverage but are effective in conjunction with the available infrastructure. This finding has important implications for achieving full immunisation coverage, which stems from the sharing of responsibilities between the central and state governments under India's federalised system of government. © 2020 Economic and Political Weekly. All rights reserved.

Economic and Political Weekly

Policy complementarities in achieving universal immunisation coverage in India

Fulltext

Frontiers in Computational Neuroscience

Editorial: Temporal Structure of Neural Processes Coupling Sensory, Motor and Cognitive Functions of the Brain

We consider an M/ M/ 1 / N¯ observable non-customer-intensive service queueing system with unknown service rates consisting of strategic impatient customers who make balking decisions and non-strategic patient customers who do not make any decision. In the queueing game amongst the impatient customers, we show that there exists at least one pure threshold strategy equilibrium in the presence of patient customers. As multiple pure threshold strategy equilibria exist in certain cases, we consider the minimal pure threshold strategy equilibrium in our sensitivity analysis. We find that the likelihood ratio of a fast server to a slow server in an empty queue is monotonically decreasing in the proportion of impatient customers and monotonically increasing in the waiting area capacity. Further, we find that the minimal pure threshold strategy equilibrium is non-increasing in the proportion of impatient customers and non-decreasing in the waiting area capacity. We also show that at least one pure threshold strategy equilibrium exists when the waiting area capacity is infinite. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

Queueing Systems

Equilibrium in a finite capacity M/M/1 queue with unknown service rates consisting of strategic and non-strategic customers

In this paper we discuss the simple bilevel programming problem (SBP) and its extension, the simple mathematical programming problem under equilibrium constraints (SMPEC). Here we first define both these problems and study their interrelations. Next we study the various types of necessary and sufficient optimality conditions for the (SMPEC) problems, which occur under various reformulations. The optimality conditions for (SBP) are special cases of the results obtained for (SMPEC) when the lower level objective is the gradient of a convex function. Among the various optimality conditions presented in this article are the sequential optimality conditions, which do not need any constraint qualification. We also present a schematic algorithm for (SMPEC), where the sequential optimality conditions play a key role in the convergence analysis. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society.

Mathematical Programming

Simple bilevel programming and extensions

The main goal in this paper is to devise an approach to explicitly calculate the constant in the Hoffman’s error bound for (not necessarily convex) inequality systems defining convex sets. We give a constructive proof of the Hoffman’s error bound and show that we can use our method to calculate the constant at least in simple cases. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society.

Error bounds for inequality systems defining convex sets

In this article we focus on algorithms for solving simple bilevel programming problems. Simple bilevel problems consist of minimizing a convex function over the solution set of another convex optimization problem. Though the problem is convex the bilevel structure prevents the direct application of the standard methods of convex optimization. Hence several algorithms have been developed in the literature to tackle this problem. In this article we discuss several such algorithms including recent ones. © 2020, Springer Nature Switzerland AG.

Springer Optimization and Its Applications

Algorithms for Simple Bilevel Programming

Perception necessitates interaction among neuronal ensembles, the dynamics of which can be conceptualized as the emergent behavior of coupled dynamical systems. Here, we propose a detailed neurobiologically realistic model that captures the neural mechanisms of inter-individual variability observed in cross-modal speech perception. From raw EEG signals recorded from human participants when they were presented with speech vocalizations of McGurk-incongruent and congruent audio–visual (AV) stimuli, we computed the global coherence metric to capture the neural variability of large-scale networks. We identified that participants' McGurk susceptibility was negatively correlated to their alpha band global coherence. The proposed biophysical model conceptualized the global coherence dynamics emerge from coupling between the interacting neural masses—representing the sensory-specific auditory/visual areas and modality nonspecific associative/integrative regions. Subsequently, we could predict that an extremely weak direct AV coupling results in a decrease in alpha band global coherence—mimicking the cortical dynamics of participants with higher McGurk susceptibility. Source connectivity analysis also showed decreased connectivity between sensory-specific regions in participants more susceptible to McGurk effect, thus establishing an empirical validation to the prediction. Overall, our study provides an outline to link variability in structural and functional connectivity metrics to variability of performance that can be useful for several perception and action task paradigms. © 2020 Federation of European Neuroscience Societies and John Wiley & Sons Ltd

European Journal of Neuroscience

Biophysical mechanisms governing large-scale brain network dynamics underlying individual-specific variability of perception

Inspired by the interactive discrete choice logit models [Aggarwal, 2019], this paper presents the advanced families of discrete choice models, such as nested logit, mixed logit, and probit models to consider the interaction among the attributes. Besides the DM’s attitudinal character is also taken into consideration in the computation of choice probabilities. The proposed choice models make use of Choquet integal and the recent attitudinal Choquet integral. The models are termed as Choquet nested logit (CNL), Choquet mixed multinomial logit (CMMNL), and Choquet multinomial probit (CMP). These are further extended to represent the DM’s attitudinal character, and termed as attitudinal CNL, attitudinal CMMNL, and attitudinal CMP. © 2020, University of Sistan and Baluchestan. All rights reserved.

Iranian Journal of Fuzzy Systems

Probit and nested logit models based on fuzzy measure

Often in real-world decision making, it is difficult to crisply evaluate the utility values as required in the case of conventional choice models. Besides, a decision maker (DM) has his/her own relative importance for each of the attributes. The attributes may also be interacting positively (synergy) or negatively, the degree of which is specific to the DM. A new family of discrete choice models is introduced with a motivation that takes into account the human factors in real-world multiattribute decision making. More specifically, the proposed choice models are based on fuzzy subjective utilities that are easier to elicit. The proposed models are further extended to take into account the unique attitudinal character of the DM, the relative weight vector, and the degree of interaction among the different attributes. A real case study illustrates the usefulness of the study. © 1993-2012 IEEE.