Editorial from the Editor-in-Chief regarding this case of plagiarism

Philippe Mahey

1 Introduction

Plagiarism is a plague that any scientific publication in any discipline should fight and eradicate all over the world. Unfortunately, if, on the one hand, the powerful search engines available on the web have helped referees to identify most of the cases, the increasing number of publications have on the other hand facilitated that dubious practice and the number of cases have increased. The case we are facing today in our journal is a severe one as the "authors" are multi-recidivists who have been identified in former plagiarized papers since 2007. M. Sreenivas and T. Srinivas have this time succeeded in obtaining the publication of a plagiarized paper in the last issue of the RAIRO journal, but their fraud has been identified very quickly by different colleagues. We will briefly recall below the history of former cases involving these two persons and expose the proofs of plagiarism about the current paper which justify its retraction from the records of the journal.

2 A history of frauds

At least four papers co-authored by Sreenivas and Srinivas have been revealed in the last two years and a report about this investigation has been published on the web page of SIAM (http://www.siam.org/journals/plagiary/index.php). The method was nearly always the same as these papers contained entire paragraphs and abstracts copied almost verbatim from preprints or old papers in the field (the Transportation area). We will only resume one of these facts which is particularly instructive: as mentioned in the SIAM report, the paper: M. Sreenivas and T. Srinivas, The transportation: more-for-less criterion, International Journal of Statistics and Management System, v. 3, n. 1–2, pp. 152–165, 2008 is indeed plagiarized from S. Storøy: The transportation paradox revisited, posted to Optimization Online September 2007. Surprisingly, the same authors have submitted the same paper in parallel to the 4OR journal in october 2007, but it was discovered to be plagiarized and was not published. The editors of that journal published an editorial in the first number of the 2009 volume (D. Bouyssou, S. Martello, F. Plastria, Plagiarism again: Sreenivas and Srinivas, and an update on Marcu, 4OR vol. 7, n°1, 2009, pp. 17–20) with a transcription of the exchange mail between them and the authors where the latter did express some weak regrets without any further justification. As said in the editorial, "this did not prevent them from submitting their plagiarized text to another well-known OR journal, namely the European Journal of Operations Research" Unfortunately enough, the 4OR editorial was published too late to prevent the publication of the present paper in RAIRO.

3 The plagiarized paper

The applied procedure for this kind of plagiarism is always the same: select and copy paragraphs and sentences from textbooks or research reports, and finally merge them in a personal form that is able to mislead the reader. The following references prove that the paper "A short note on marginal analysis of a transportation problem", published in vol. 43, n°4, pp. 331–337, has been almost entirely plagiarized:

1. The entire abstract after the first sentence is a verbatim copy of a paragraph from "Deterministic modeling: linear optimization with applications", a set of course notes by Hossein Arsham.  The paragraph in question can be found at: http://home.ubalt.edu/ntsbarsh/opre640a/partVIII.htm#rmarginalFactorPri

2. The first paragraph of the introduction is taken from course notes posted by Tim Yeager at http://sorrel.humboldt.edu/%7Eeconomic/econ104/marginal/

3. The second paragraph is taken verbatim from http://www.papercamp.com/essays/Decision-Making/3884.html

4. Section 2 is a verbatim copy from K. Murty well-known textbook: http://ioe.engin.umich.edu/people/fac/books/murty/opti_model/junior-6.pdf

5. The first illustration of section 3 is taken too from Murty’s book.

6. The first paragraph of the conclusion comes from the same source as the introduction.

7. None of the references are actually referred to in the paper.

We have asked the authors of the plagiarism to explain the situation and defend themselves. Their answer was that they found normal to refer to other research papers to present the concepts. They add that "A small misunderstanding is that the sources of the taken matter are not mentioned in the article. It never repeat again". We understand in their poor defence that they plead guilty and promise to stop plagiarizing, but the long history of frauds we have reported above shows that we cannot trust them and must ban them from publishing in RAIRO.

4 Conclusion

We hope that the plagiarism activities of Sreenivas and Srinivas will now definitively stop. The above plagiarized paper will be retracted from the electronic records of the RAIRO Journal. They are now banned from publishing in an international OR journal for the second time and their former attempts are now well referenced and diffused so that the whole community, from Transportation, Operations Research and Applied Mathematics areas, will have the right tools to foil their future submissions if any.

Acknowledgements: We thank heartily the former editors of 4OR, Denis Bouyssou, Silvano Martello and Frank Plastria for identifying the plagiarism, and Douglas Arnold, President of SIAM, for his help and advice in dealing with the present plagiarism.

This paper investigates the problem of maximizing the revenue of a telecommunications operator by simultaneously pricing point-to-point services and allocating bandwidth in its network, while facing competition. Customers are distributed into market segments, i.e., groups of customers with a similar preference for the services. This preference is expressed using utility functions, and customers choose between the offers of the operator and of the competition according to their utility. We model the problem as a leader-follower game between the operator and the customers. This kind of problem has classically been modeled as a bilevel program. A market segmentation is usually defined by a discrete distribution function of the total demand for a service; in this case, the problem can be modeled as a combinatorial optimization problem. In this paper, however, we motivate the use of a continuous distribution function and investigate the nonlinear continuous optimization problem obtained in this case. We analyze the mathematical properties of the problem, and in particular we give a necessary and sufficient condition for its convexity. We introduce methods to solve the problem and we provide encouraging numerical results on realistic telecommunications instances of the problem, showing that it can be solved efficiently.

In this paper, we face a generalization of the problem of finding the distribution of how long it takes to reach a “target” set T of states in Markov chain. The graph problems of finding the number of paths that go from a state to a target set and of finding the n-length path connections are shown to belong to this generalization. This paper explores how the state space of the Markov chain can be reduced by collapsing together those states that behave in the same way for the purposes of calculating the distribution of the hitting time of T. We prove the existence and the uniqueness of a optimal projection for this aim which extends the results given in [G. Aletti and E. Merzbach, J. Eur. Math. Soc. (JEMS)8 (2006) 49–75], together with the existence of a polynomial algorithm which reaches this optimum. Some applied examples are presented. Markov complexity is defined an tested on some classical problems to demonstrate the deeper understanding that is made possible by this approach.

The multiparametric 0-1-Integer Programming (0-1-IP) problem relative to the objective function is a family of 0-1-IP problems which are related by having identical constraint matrix and right-hand-side vector. In this paper we present an algorithm to perform a complete multiparametric analysis relative to a generalized min max objective function such that the min sum and min max are particular cases.

Le Problème du Vendeur m-Péripatétique (m-PVP) est défini sur un graphe non orienté G=(V,E) où V = {1,...,n} est l'ensemble des sommets, E = {(i,j) : i,j ∈ V,i < j} est l'ensemble des arêtes et (cij) est une matrice de coûts définie sur E. Le m-PVP consiste à déterminer m cycles hamiltoniens sur G n'ayant aucune arête en commun et dont le coût total est minimal. Cet article décrit sept nouvelles heuristiques pour le m-PVP et les compare à celle qui a été proposée par Krarup en 1975.

On étudie à l'aide du système AutoGraphiX 2 (AGX 2) des relations de la forme \[ \underline{b}_{n} \, \le \, g \, \oplus \, i \, \le \, \overline{b}_{n} \] où g désigne la maille d'un graphe G=(V, E), i un autre invariant parmi la distance moyenne $\overline{l}$, l'index λ1, l'indice de Randić R et le nombre de domination β, $\oplus$ désigne l'une des opérations +, -, ×, /, $\underline{b}_{n}$ et $\overline{b}_{n}$ des fonctions de l'ordre n du graphe qui bornent l'expression $g\oplus i$ et sont atteintes pour tout n (sauf éventuellement de très petites valeurs du fait des effets de bord). Les résultats prouvés ou discutés ci-dessous ont déjà été présentés, sous forme de conjectures, dans un article précédent paru dans RAIRO Recherche Opérationnelle [RAIRO Oper. Res. 39 (2005) 275–293].

Starting from the famous Königsberg bridge problem which Euler described in 1736, we intend to show that some results obtained 180 years later by König are very close to Euler's discoveries.

The aim of this paper is to show a polynomial algorithm for the problem minimum directed sumcut for a class of series parallel digraphs. The method uses the recursive structure of parallel compositions in order to define a dominating set of orders. Then, the optimal order is easily reached by minimizing the directed sumcut. It is also shown that this approach cannot be applied in two more general classes of series parallel digraphs.

In the paper we generalize sufficient and necessary optimality conditions obtained by Ginchev, Guerraggio, Rocca, and by authors with the help of the notion of ℓ-stability for vector functions.

This paper aims at proposing tractable algorithms to find effectively good solutions to large size chance-constrained combinatorial problems. A new robust model is introduced to deal with uncertainty in mixed-integer linear problems. It is shown to be strongly related to chance-constrained programming when considering pure 0–1 problems. Furthermore, its tractability is highlighted. Then, an optimization algorithm is designed to provide possibly good solutions to chance-constrained combinatorial problems. This approach is numerically tested on knapsack and multi-dimensional knapsack problems. The results obtained outperform many methods based on earlier literature.

Given a tree T with n vertices, we show, by using a dynamic programming approach, that the problem of finding a 3-coloring of T respecting local (i.e., associated with p prespecified subsets of vertices) color bounds can be solved in O(n6p-1logn) time. We also show that our algorithm can be adapted to the case of k-colorings for fixed k.

This paper studies the machine repair problem consisting of M operating machines with S spare machines, and R servers (repairmen) who leave for a vacation of random length when there are no failed machines queuing up for repair in the repair facility. At the end of the vacation the servers return to the repair facility and operate one of three vacation policies: single vacation, multiple vacation, and hybrid single/multiple vacation. The Markov process and the matrix-geometric approach are used to develop the steady-state probabilities of the number of failed machines in the system as well as the performance measures. A cost model is developed to obtain the optimal values of the number of spares and the number of servers while maintaining a minimum specified level of system availability. Some numerical experiments are performed and some conclusions are drawn.

Soit F une famille de critères conçue pour asseoir un modèle de préférences global sur un ensemble A d'actions potentielles (ou alternatives). On se place ici dans une perspective d'aide à la décision et dans l'hypothèse où des dépendances (encore appelées interactions) sont susceptibles d'exister entre certains des critères de F. On commence (cf. Sect. 2.1) par préciser ce que signifie l'affirmation "il existe des dépendances entre certains des critères de F" (Déf. 1). On s'intéresse ensuite à deux formes classiques de dépendances (cf. Sect. 2.2). Dans la Section 3, on cherche à apporter des éléments de réponse à la question : comment mettre en évidence les dépendances s'il en existe et comment les rendre intelligibles pour les parties prenantes au processus de décision ? On définit trois types de situations particulièrement dignes d'intérêt car aisément intelligibles et faciles à cerner. Dans la section suivante, on examine les possibilités qu'offrent un certain nombre de modèles d'agrégation pour prendre en compte explicitement des dépendances. On met notamment en évidence (cf. Sect. 4.2) les possibilités et limites de l'intégrale de Choquet. Tout au long de l'article, des exemples sont introduits pour illustrer les propos.


Recently, Y.Q. Bai, M. El Ghami and C. Roos [3] introduced a new class of so-called eligible kernel functions which are defined by some simple conditions. The authors designed primal-dual interior-point methods for linear optimization (LO) based on eligible kernel functions and simplified the analysis of these methods considerably. In this paper we consider the semidefinite optimization (SDO) problem and we generalize the aforementioned results for LO to SDO. The iteration bounds obtained are analogous to the results in [3] for LO.

A reformulation of a mathematical program is a formulation which shares some properties with, but is in some sense better than, the original program. Reformulations are important with respect to the choice and efficiency of the solution algorithms; furthermore, it is desirable that reformulations can be carried out automatically. Reformulation techniques are widespread in mathematical programming but interestingly they have never been studied under a unified framework. This paper attempts to move some steps in this direction. We define a framework for storing and manipulating mathematical programming formulations and give several fundamental definitions categorizing useful reformulations in essentially four types (opt-reformulations, narrowings, relaxations and approximations). We establish some theoretical results and give reformulation examples for each type.

In this paper, we describe the methodology used to tackle France Telecom workforce scheduling problem (the subject of the Roadef Challenge 2007) and we report the results obtained on the different data sets provided for the competition. Since the problem at hand appears to be NP-hard and due to the high dimensions of the instance sets, we use a two-step heuristical approach. We first devise a problem-tailored heuristic that provides good feasible solutions and then we use a meta-heuristic scheme to improve the current results. The tailored heuristic makes use of sophisticated integer programming models and the corresponding sub-problems are solved using CPLEX while the meta-heuristic framework is a randomized local search algorithm. The approach herein described allowed us to rank 5th in this challenge.

Ce travail porte sur l'optimisation des lignes d'usinage pour la grande série. Une telle ligne comporte plusieurs postes de travail, chacun étant équipé avec boîtiers multibroches. Un boîtier multibroche exécute plusieurs opérations en parallèle. Lors de la conception en avant-projet, il est nécessaire d'affecter toutes les opérations à des boîtiers et des postes de travail de sorte à minimiser le nombre de postes et de boîtiers utilisés. Pour ce nouveau problème d'équilibrage des lignes de production, nous proposons une approche de résolution par décomposition en utilisant des méthodes exactes et heuristiques. Les résultats des tests numériques effectués sur des instances proches des problèmes réels sont présentés et analysés.

In this work, we study an optimal control problem dealing with differential inclusion. Without requiring Lipschitz condition of the set valued map, it is very hard to look for a solution of the control problem. Our aim is to find estimations of the minimal value, (α), of the cost function of the control problem. For this, we construct an intermediary dual problem leading to a weak duality result, and then, thanks to additional assumptions of monotonicity of proximal subdifferential, we give a more precise estimation of (α). On the other hand, when the set valued map fulfills the Lipshitz condition, we prove that the lower semicontinuous (l.s.c.) proximal supersolutions of the Hamilton-Jacobi-Bellman (HJB) equation combined with the estimation of (α), lead to a sufficient condition of optimality for a suspected trajectory. Furthermore, we establish a strong duality between this optimal control problem and a dual problem involving upper hull of l.s.c. proximal supersolutions of the HJB equation (respectively with contingent supersolutions). Finally this strong duality gives rise to necessary and sufficient conditions of optimality.