Annals Of Operations Research Research Articles

PAST, PRESENT AND FUTURE OF DIGITALIZATION OF LOGISTIC OPERATION: A BIBLIOMETRIC ANALYSIS

This paper aims to analyze the digitalization-logistic operation-related literature from 1995 to 2021 using the bibliometric technique. This article analyses 266 papers from the Web of Science database and the database consisted of peer-reviewed journal articles, reviews, and early accesses articles. Moreover, Bibliometrix R-Package software is used to map the bibliographic material. The research revealed that: the number of publications steadily increased after 2017 and Engineering and Business and Economies are the most productive research areas. China, the USA and Germany are the most productive country based on the total publications and total citations. Indeed, when analyzing the academic collaborative relationships among countries, China is the center of international collaboration and mostly works with the UK and the USA. Furthermore, “Sustainability” is the most productive journal, “International Journal of Production Research” has the highest impact factor and “Annals of Operations Research” has the highest total citation. Besides, Jinan University is the most productive institution and Ivanov D. is one of the most academically influential author in the research area. According to keyword analysis, “logistics”, “management” and “performance” keywords are frequently used by authors.

M. Gabriela Sava Finalist of the 2020 MCDM Junior Researcher Best Paper Award

In April 2020, M. Gabriela Sava received the great news that her paper “An analysis of the sensitivity and stability of patients’ preferences can lead to more appropriate medical decisions,” published in Annals of Operations Research was selected as a finalist for the 2020 MCDM Junior Researcher Best Paper Award. The paper was in collaboration with Dr. Luis G. Vargas and Dr. Jerrold H. May from University of Pittsburgh and Dr. James G. Dolan from University of Rochester Medical Center. The award honors junior academic researchers and practitioners who work in the area of multi-criteria decision-making for their excellence, creativity and innovation. Gabriela was nominated for this prestigious award by the Associate Editor of the IJAHP, Dr. Birsen Karpak from Youngstown State University.

Preface: sustainable operations in manufacturing enterprise

Article published in Annals of Operations Research on 12 June 2020, available at: https://doi.org/10.1007/s10479-020-03679-5.

Discrete analogues of continuous multivariate probability distributions

In this note we introduce multivariate extensions to the bivariate discrete analogue to continuous probability distributions proposed in Barbiero [Annals of Operations Research, doi: 10.1007/s10479-019-03388-8, 2019]. We furthermore show that identical properties of the bivariate case also hold for n-variate discrete analogues.

Preface: International conference on game theory and optimization, June 6–10, 2016, Indian Institute of Technology Madras, Chennai, India

A conference-cum-workshop on Game Theory and Optimization was held at the Indian Institute of Technology Madras, during June 6–10, 2016. One of the primary objectives of the event was to commemorate the 75th birthday of Professor T. Parthasarathy, fondly referred to as TP. A special session was devoted to his life and mathematical career. This provided a platform for many of TP’s students and collaborators to share their experiences with the audience. The conference was made possible through funding from the National Mathematics Initiative. Additional funding was received from the Office of Alumni and International Relations, the Departments of Mathematics, and Management Studies, Indian Institute of Technology Madras (IIT Madras). Following is a brief overview of the contributions to this special issue, a biography of Professor TP, and a list of his publications. The Guest Editors would like to thank all the authors, Annals of Operations Research Editor-in-Chief, Endre Boros, and all referees who provided peer review. This special issue would not have been possible without their valuable time and input.

Bubble regime identification in an attention-based model for Bitcoin and Ethereum price dynamics

In this paper we extend the model in Cretarola, Figà-Talamanca, “Detecting bubbles in Bitcoin price dynamics via market exuberance”, Annals of Operations Research (2019), by allowing for a state-dependent correlation parameter between asset returns and market attention. We assume that the change of state is described by a continuous time latent Markov chain and we propose an estimation procedure based on the conditional maximum likelihood and on the Hamilton filter. Finally, model parameters, as well as Markov chain transition probabilities, are estimated on Bitcoin and Ethereum returns in case market attention is measured via the Google Search Volume Index for the keywords “bitcoin” and “ethereum”, respectively; up to four regimes are considered in the empirical application. The empirical outcomes show that the model is not only capable of identifying bubble and non-bubble regimes but also enables the interpretation of the correlation between cryptocurrencies and their market attention as a tuning to define the speed at which a bubble boosts.

On the distribution-free continuous review (Q, r, L) inventory model with lead-time-dependent partial backlogging

ABSTRACTIn this article, we study a distribution-free continuous review inventory system that assembles lost sales and backorders. The order quantity, the reorder point and lead-time are decision variables of the problem. The study under consideration assumes that purchasing cost is order dependent, partial backlogging is lead-time dependent and the distribution of lead-time demand is known partially. The objective of the paper is twofold. First, in the random framework, we provide the optimal order quantity, reorder level and lead-time simultaneously to acquire significant savings in the total costs of the model than Sana and Goyal ((q, r, l) model for stochastic demand with lead-time dependent partial backlogging. Annals of Operations Research. 233(1), 401–410, 2015). Second, we extend the crisp model to the fuzzy random environment employing the uncertain demand rate as a fuzzy random variable. We develop the mathematical methodologies to obtain the optimal solutions such that the total expected cost of the inventory system is minimized in both the cases. An algorithm is proposed with the help of the developed methodologies. We employ the proposed algorithm to solve two numerical examples to demonstrate the effectiveness of the methods.

Preface: operations research for transportation

Transportation is a broad multidisciplinary science concerned with the study of transportation network design, vehicle application engineering, as well as transportation operations and management. Due to the breadth of the topic and the increasing complexity of the decision processes involved in managing transportation operations, transportation has become a fertile field of study for operations research. Inspired by this, we have compiled this special issue of the Annals of Operations Research comprising of 24 new research contributions and two systematic literature reviews supporting and categorizing the current state of transportation research.

Hierarchical modeling of graphs using modular decomposition

Hierarchical modeling of graphs using modular decomposition

Two short proofs regarding the logarithmic least squares optimality in Chen, K., Kou, G., Tarn, J. M., Song, Y. (2015): Bridging the gap between missing and inconsistent values in eliciting preference from pairwise comparison matrices, Annals of Operations Research 235(1):155–175

Two short proofs regarding the logarithmic least squares optimality in Chen, K., Kou, G., Tarn, J. M., Song, Y. (2015): Bridging the gap between missing and inconsistent values in eliciting preference from pairwise comparison matrices, Annals of Operations Research 235(1):155–175

Novel theory and methodology developments in data envelopment analysis

This is a post-peer-review, pre-copyedit version of an article published in Annals of Operations Research. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10479-017-2413-7

Preface

International Game Theory ReviewVol. 17, No. 02, 1502002 (2015) Special Issue on Applied Optimization and Game-Theoretic Models (Part II); Guest Editors: S. K. Neogy, T. Parthasarathy and A. K. DasNo AccessPrefaceS. K. Neogy, T. Parthasarathy, and A. K. DasS. K. NeogyIndian Statistical Institute, 7, S.J.S. Sansanwal Marg, New Delhi: 110016, India, T. ParthasarathyChennai Mathematical Institute, Chennai, India, and A. K. DasIndian Statistical Institute, 203, B. T. Road, Kolkata, Indiahttps://doi.org/10.1142/S0219198915020028Cited by:1 Next AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail FiguresReferencesRelatedDetailsCited By 1Preface: International conference on game theory and optimization, June 6–10, 2016, Indian Institute of Technology Madras, Chennai, IndiaK. C. Sivakumar, M. S. Gowda, G. Ravindran and Usha Mohan13 February 2020 | Annals of Operations Research, Vol. 287, No. 2 Recommended Vol. 17, No. 02 Metrics History Accepted 12 September 2014 Published: 16 March 2015 PDF download

Editorial: Optimization of Maintenance Activities—Models, Methods, and Applications

The present special volume of the Annals of Operations Research consists of articles submitted to the Journal following the workshop Optimization of Maintenance Activities— Models, Methods and Applications, which was held at the Department of Mathematical Sciences, ChalmersUniversity of Technology andUniversity ofGothenburg, Goteborg, Sweden, December 10–11, 2009. Performing the right maintenance activities is crucial for the safety, reliability, availability, and profitability of a large range of operations and activities; it is also increasingly widely recognized as important for the sustainability of vital resources. The purpose of theworkshop, which gathered 34 participants from several countries as well as from several academic and industrial fields, was to discuss the state-of-the-art and future challenges and possibilities in modelling and solving these problems, and of applying their solutions. During the workshop there were interesting and stimulating discussions on detailed modelling and analysis questions, as well as on across subject boundaries, including problems associatedwith the practical implementation of solutions frommathematical models ofmaintenance problems. The presentations covered operations research-based modeling and analysis approaches to important maintenance problems. Theory and applications, case studies, as well as tutorials on state-of-the-art practices and methods were presented. During the two days two plenary talks and twelve regular presentations were given; articles based on six of the latter are published in this volume. The first plenary talk, entitled “On the optimization of condition-based maintenance decisions”, was given by professor Andrew Jardine, Centre for Maintenance Optimization and Reliability Engineering, University of Toronto. The second plenary talk, entitled “An overview of models tackling maintenance and production”, was given by professor Rommert Dekker, Erasmus School of Economics, Rotterdam.

Editorial: collaborative environmental management and modelling

After several decades of rapid technological advancement and economic growth, levels of pollution and environmental degradation are rising all over the world. Unilateral response on the part of one single country would hardly be effective. Collaborations in pollution abatement, R&D in technology development, emissions reduction, and subsidization for technology transfer offer the best promise to assist the development of an effective means to halt the accelerating trend of environmental deterioration. International cooperative agreements have to be negotiated to deal with the global environmental problem. In these negotiations, intraand inter-generational cost sharing, compensation for technology transfer, gains distribution, and sustainability are among the important issues to be resolved and pose an ensemble of problems that are best addressed through strategic modelling. Applications of operations research methodologies—such as optimization techniques, control theory, and interactive strategic analysis—are crucial to the development of collaborative environmental management paradigms and the formulation of viable solutions. This special volume of the Annals of Operations Research contains a collection of frontier research papers on operations research techniques and practicable solutions in environmental modeling and collaborative management. In the paper of Finus et al., the stability of self-enforcing climate agreements under a sequential coalition formation process of heterogeneous and farsighted players is studied. In particular, players can make proposals that are either accepted or countered by alternative

The practice and theory of automated timetabling

This special volumecomprises revisedversions of a selectionof the papers thatwere presented at the 9th International Conference on the Practice and Theory of Automated Timetabling (PATAT) in Belfast between 10th and 13th August 2010. The PATAT conferences are held biennially and this is the second time that the Annals of Operations Research has provided the venue for such a special collection of papers. The first PATAT special volume of this journal (Volume 194) contains papers associated with the 8th conference which was held in Montreal in 2008. PATAT acts as an international forum for all aspects of timetabling, including educational timetabling, personnel rostering, sports timetabling, and transport scheduling. The conference series is particularly concerned both with closing the gap between timetabling theory and practice and with supporting multidisciplinary interactions. The collection of papers in this special volume reflect these aims. The conference in Belfast brought together approximately 100 participants from around the world. There were five plenary presentations, 74 standard talks, and 16 practitioner presentations. All the delegates were invited to submit their revised papers to this special volume. The papers have been through a rigorous and thorough review process, and we are delighted to be able to present the community with such an interesting and diverse selection of articles that reflect the latest thinking in timetabling research. We would like to take this opportunity to thank all those who were responsible for the success of the conference. We would particularly like to thank Brian Fleming and all those within the School of Electronics, Electrical Engineering andComputer Science at theQueen’s University of Belfast who worked so hard before and during the conference.

Influential DMUs and outlier detection in data envelopment analysis with an application to health care

This paper explains some drawbacks on previous approaches for detecting influential observations in deterministic nonparametric data envelopment analysis models as developed by Yang et al. (Annals of Operations Research 173:89-103, 2010). For example efficiency scores and relative entropies obtained in this model are unimportant to outlier detection and the empirical distribution of all estimated relative entropies is not a Monte-Carlo approximation. In this paper we developed a new method to detect whether a specific DMU is truly influential and a statistical test has been applied to determine the significance level. An application for measuring efficiency of hospitals is used to show the superiority of this method that leads to significant advancements in outlier detection.

Robustness of optimal portfolios under risk and stochastic dominance constraints

Solutions of portfolio optimization problems are often influenced by a model misspecification or by errors due to approximation, estimation and incomplete information. The obtained results, recommendations for the risk and portfolio manager, should be then carefully analyzed. We shall deal with output analysis and stress testing with respect to uncertainty or perturbations of input data for static risk constrained portfolio optimization problems by means of the contamination technique. Dependence of the set of feasible solutions on the probability distribution rules out the straightforward construction of convexity-based global contamination bounds. Results obtained in our paper [Dupačová, J., & Kopa, M. (2012). Robustness in stochastic programs with risk constraints. Annals of Operations Research, 200, 55–74.] were derived for the risk and second order stochastic dominance constraints under suitable smoothness and/or convexity assumptions that are fulfilled, e.g. for the Markowitz mean–variance model. In this paper we relax these assumptions having in mind the first order stochastic dominance and probabilistic risk constraints. Local bounds for problems of a special structure are obtained. Under suitable conditions on the structure of the problem and for discrete distributions we shall exploit the contamination technique to derive a new robust first order stochastic dominance portfolio efficiency test.

Applications of operations research in educational measurement

The educational testing industry has grown significantly over the past few decades. The No Child Left Behind Act of 2002 has required each state to assess the educational quality of its public schools. Also, most higher education institutions consider scores on standardized tests in their admission decisions, and most assess general academic achievement with additional testing. Thus, reliable tests and proper interpretation of the results are vital to today’s entire educational community. More specifically, it is essential to analyze consistently the quality of test questions, the feedback from the test scores, the reliability of test scores, and the results of validation studies. This special section of the Annals of Operations Research concentrates on the use of operations research (OR) within the educational measurement industry. It has the following objectives, bridging two different research communities:

Strong NP-hardness of scheduling problems with learning or aging effect

Proofs of strong NP-hardness of single machine and two-machine flowshop scheduling problems with learning or aging effect given in Rudek (Computers & Industrial Engineering 61:20–31, 2011; Annals of Operations Research 196(1):491–516, 2012a; International Journal of Advanced Manufacturing Technology 59:299–309, 2012b; Applied Mathematics and Computations 218:6498–6510, 2012c; Applied Mathematical Modelling 37:1523–1536, 2013) contain a common mistake that make them incomplete. We reveal the mistake and provide necessary corrections for the problems in Rudek (Computers & Industrial Engineering 61:20–31, 2011; Annals of Operations Research 196(1):491–516, 2012a; Applied Mathematical Modelling 37:1523–1536, 2013). NP-hardness of problems in Rudek (International Journal of Advanced Manufacturing Technology 59:299–309, 2012b; Applied Mathematics and Computations 218:6498–6510, 2012c) remains unknown because of another mistake which we are unable to correct.

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